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10. The system of claim 8 wherein determining the accuracy of the translation based on a combination of the probabilities comprises: linearly interpolating the probabilities to generate the accuracy.

11. The system of claim 10 wherein linearly interpolating the probabilities to generate the accuracy comprises: weighting the probabilities of the POS n-grams according to their lengths wherein POS n-grams having lengths greater than other POS n-grams are weighted more than the other POS n-grams.

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17. The computer-readable medium of claim 15 , wherein the set of one or more context uniform resource identifiers includes uniform resource identifiers associated with one or more of a favorites list, a positive preference list, or a negative preference list.

15. A non-transitory computer-readable medium having stored thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations comprising: identifying, by a browser assistant, a set of one or more context uniform resource identifiers; receiving, by the browser assistant, a set of one or more referenced uniform resource identifiers that are referenced by a search results page provided by a search engine; for each referenced uniform resource identifier, determining, by the browser assistant, a relatedness score based on an extent to which the referenced uniform resource identifier is related to one or more of the context uniform resource identifiers; selecting, by the browser assistant, a subset of the referenced uniform resource identifiers for presentation based on the relatedness scores; and providing, by the browser assistant, the subset of the referenced uniform resource identifiers for presentation as a web page in a browser window.

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23. The system of claim 21 , wherein the processor circuitry is further configured to compare the live image against a collection of at least one sample image to determine the object of interest.

24. The system of claim 23 , wherein the processor circuitry is further configured to use optical character recognition to learn about textual image content.

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4. The system of claim 1 in which the computer implemented boundary selection sub-system identifies a portion of the audio message that contains an address, and wherein the portion is sent to an ASR component specially configured to automatically recognize addresses.

1. A voice messaging system for converting an audio voice message from a caller to a recipient to text, the voice messaging system comprising: an automatic speech recognition (ASR) system to automatically recognize at least some of the audio voice message, the ASR system comprising: a plurality of ASR components, each specially configured to recognize a respective type of content; and a computer implemented boundary selection sub-system to process the audio voice message to identify at least one portion of the audio voice message which contains content of the type for which one of the plurality of ASR components is specially configured, wherein the identified at least one portion of the audio message is sent to the one of the plurality of ASR components specially configured for the type of content identified in the at least one portion to be automatically recognized.

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4. The method of claim 1 , further comprising: automatically updating a ranking of at least a portion of the plurality of user-created keywords.

1. A method for creating presenting keywords used for a review of an item, the method comprising: obtaining a plurality of user-created keywords, wherein each user-created keyword is created by a user in a review; receiving votes to indicate users' ratings of effectiveness of the user-created keywords used in reviews; transferring at least a portion of the plurality of user-created keywords for display to a user, wherein a digital processor is used to display the user-created keywords on a display screen in association with a category along with a rating for each keyword, wherein the rating is derived from the votes, wherein the rating includes a number indicating the amount of times that the keyword has been used in other reviews about the item; and accepting a signal from a user input device operated by the user to select at least one of the plurality of user-created keywords for use in a new review about the item being created by the user.

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17. A non-transitory computer-readable storage medium having computer-executable instructions for detecting a network activity of interest, computer-executable instructions comprising instructions for: obtaining a plurality of network packets from a network, wherein the obtained plurality of network packets includes the network activity of interest; creating a plurality of combined packets from the plurality of network packets, wherein the plurality of combined packets includes: a first combined packet, and a second combined packet different from the first combined packet; creating, by the one or more processors, a first sequence by converting content of at least a portion of the first combined packet into a first plurality of integers, wherein the first sequence includes the first plurality of integers; creating, by the one or more processors, a second sequence by converting content of at least a portion of the second combined packet into a second plurality of integers, wherein the second sequence includes the second plurality of integers; determining a similarity metric between the first sequence and the second sequence based on a distance function; creating a third sequence based on the similarity metric, wherein the third sequence comprises a third plurality of integers common to the first sequence and the second sequence, in a first order, wherein the third sequence is a meta-expression that corresponds to the presence of the network activity of interest in the network traffic; and storing the meta-expression, wherein the stored meta-expression is used to detect the presence of the network activity of interest.

29. The non-transitory computer-readable medium of claim 17 , wherein the stored meta-expression is stored on a first computing device, and wherein the computer-executable instructions comprises instructions for: detecting, by the first computing device, the network activity of interest using the stored meta-expression.

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4. The method of claim 2 , wherein the hierarchical chart representation of the case history includes a plurality of text boxes, with each box displayed in association with at least one line segment connecting the box to another box, and with each box containing a case name.

6. The method of claim 4 , wherein each box further includes a symbol indicating status of a case associated with the case name as legal authority.

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4. The computer-implemented method of claim 3 wherein identifying application storage locations associated with each confirmation turn comprises identifying application storage locations where the value was at least one of confirmed, denied and corrected.

8. The computer-implemented method of claim 4 wherein the turns are related to one or more tasks of the application, and wherein analyzing confirmation turns comprises for each identified application storage location, identifying a closest prior turn in which a value of the confirmation turn was obtained and within a selected task.

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1. A method comprising: communicating with a network server via a network; receiving, at a computing device, a selection of a word or phrase; converting, via the computing device, the word or phrase into at least one unique key value using a conversion table, the conversion table comprising at least one language key for at least one language and at least one text phrase corresponding to the language key and the unique key value; and communicating the unique key value to the network server over the network.

7. The method of claim 1 , wherein the network server being one of a plurality of network servers.

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22. A system that is configured to determine a set of rules for ordering text of a language, said system comprising: an interface configured to receive information that indicates a target order of sets of characters in text of a language; and a processor configured by program code to determine strengths of differences between the characters based on the target order, identify strings of characters that were sorted in the target order as a shorter string of characters, identify strings of characters that were sorted in the target order as a longer string of characters, determine a set of rules for ordering text of the language based on the strengths of differences between the characters, the identified strings of characters that were sorted in the target order as a shorter string, and the identified strings of characters that were sorted in the target order as a longer string, wherein the target order is a sequential ordering among the sets of characters in the text of the language.

28. The system of claim 22 , wherein the processor identifies the strings that sort as shorter strings of characters based on program code for selecting a candidate string of characters from the target order, program code for combining the candidate string of characters with at least one other character in the information to form a first combined string, program code for combining the candidate string of characters with a character that has a primary difference that is greater than or equal to the other characters in the information to form a second combined string, program code for comparing the first combined string with the second combined string result in a change of sorting order, and program code for adding the candidate string of characters to a list based on whether the second combined string results in a change of sorting order.

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1. A microprocessor controlled speech synthesizer for generating the audio information of a set of characters which includes a first subset of lower case letters and a second subset of upper case capital letters so that the operator can audibly distinguish between upper and lower case letters from an external input, said synthesizer comprising; a microprocessor unit connected to a first memory for the storage of speech data and to a second memory for the storage of externally originated input characters, said microprocessor unit comprising control means responsive to said speech data from the first memory for forming a speech pattern corresponding to said input characters; a speech generator connected to said first memory and controlled by the control means of said microprocessor for producing audio signals representing said set of characters; said microprocessor unit further comprising a character recognition means connected to said first and second memories and to said speech generator for recognizing from the externally originated input characters those characters which belong to said second subset of upper case capital letters and for introducing a first modification in the speech pattern for said characters belonging to the second subset; said first modification comprising a changing of at least one pitch component or a changing of a voice characterizing component of the speech pattern while maintaining the identity of the second subset of upper case capital letters; said microprocessor further comprising a position determining means for determing the position of at least one letter of a word made up of characters presented and for introducing a second modification in the speech pattern for said letter while maintaining its identity, said second modification comprising a modification of a pitch component and/or a voice characterizing component of the speech pattern.

5. A device as claimed in claim 1, characterized in that said one letter is the last letter of a word composed of characters presented.

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1. A method for indexing and querying XML documents stored in a relational database, the method comprising: a) allowing, by a computer, a user to choose, within a database table, one or more columns for storing XML data of a known structure; b) obtaining from the user one or more XML paths for indexed data, each of the obtained one or more XML paths being stored in a static index table; c) creating, in response to the obtained one or more XML paths, at least one dynamic index table for each static index table, the dynamic index table being updated upon data being entered into the database table; d) intercepting a user's query to process a XML expression part of the query and converting the XML expression part into one or more rows in the static index table; e) generating a new query against the dynamic indexing tables, using values obtained from the static index table, and executing the generated query; f) rewriting the user's query by transforming XML path part of the user's query expression into a format understood by a database query engine; and g) returning a result to the user, after executing the rewritten query, together with any non-XML part of the user's query, that is executed by the database query engine.

3. The method of claim 1 , wherein the static index table contains one row per XML path.

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12. A system comprising: a computer having a computer input device and a display device connected thereto; and a plurality of distributed processors communicatively coupled to the computer, wherein the computer is configured to coordinate the activities of the distributed processors, wherein each of the distributed processors is configured as a separate domain-specific knowledgebase segment and is further configured to perform a method comprising the steps of: determining that a predictor case base containing predictor rules having predictor antecedents and associated predictor consequents does not contain a predictor rule having a predictor antecedent covered by an acquired predictor context; creating one or more least-generalized predictor antecedents that are covered by the acquired predictor context; creating a corrector context using the predictor consequents associated with the one or more least-generalized predictor antecedents; determining that a corrector case base containing corrector rules having corrector antecedents and associated corrector consequents contains a corrector rule having a corrector antecedent covered by the corrector context; and firing the corrector consequent associated with the corrector antecedent covered by the corrector context.

18. The system of claim 12 , wherein each of the plurality of distributed processors are configured to further perform the steps of: determining that the corrector case base does not contain a corrector rule having a corrector antecedent covered by the corrector context; creating at least one least-generalized corrector antecedent covered by the corrector context; firing the corrector consequent associated with the corrector antecedent covered by the least-generalized corrector context if one least-generalized corrector antecedent is covered by the corrector context; and firing the corrector consequent associated with the most-recently fired rule having a corrector antecedent covered by the least-generalized corrector context.

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25. The method of claim 20 , wherein the markup language is hypertext markup language.

20. The method of claim 12 , further comprising identifying at least one font indicator associated with text within the selected portion of the first web document, wherein the step of creating the second web document includes modifying the font attribute of the associated at least one font indicator.

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1. A method comprising: generating, by a server computer, a web page; injecting, by the server computer, software code into the web page, the injected software code comprising instructions for: checking that the web page is one of a plurality of user predetermined web pages; when the web page is one of the plurality of user predetermined web pages: detecting a user-initiated search interface trigger occurring during display of the web page, the user-initiated search interface trigger not associated with an input focus of the web page or an input focus of a browser on a client computer, the detecting of the user-initiated search interface trigger comprising detecting a user of the client computer selecting text on the web page, the detecting further comprising detecting the user selecting text on the web page and detecting the user completing selection of the web page text, in direct response to the detecting of the user-initiated search interface trigger, displaying a search interface that receives as input characters of the selected text, populating the search interface with content associated with the user-initiated search interface trigger, detecting a user-initiated search execution trigger, the search execution trigger comprising the detection that the user has completed selection of the web page text, transmitting, to a search entity, in response to the detecting of the search execution trigger, a request for search results related to the content associated with the populating; transmitting, by the server computer, the web page with the injected code to the client computer.

19. The method of claim 1 , further comprising receiving, by the server computer, a parameter from the client computer, the parameter restricting operation of the software code, the parameter indicating the plurality of user predetermined web pages.

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13. The multiple citation corpus data structure of claim 1 , wherein multiple citation corpus data structure is based on a set of related words.

1. A multiple citation corpus data structure stored in a computer memory for a user specified word or phrase comprising an entry for every occurrence of the user specified word or phrase, each entry comprising: a) prior context, b) the user specified word or phrase, c) subsequent context, and d) one or more internal citations, wherein the prior context, the user specified word or phrase, and the subsequent context forming a unique quote of each entry, wherein each internal citation identifies a document and the location inside the document where the unique quote of the entry is found in a plurality of formatted documents, and wherein the one or more internal citations of each entry is a combined citation comprising a complete list of every occurrence of the unique quote of the respective entry in the respective plurality of formatted documents.

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10. The electronic search system of claim 1 , wherein detecting user input selecting the first search result included in the display of the first list of search results comprises detecting user input selecting the first link of the first search result included in the display of the first list of search results, the selection of the first link of the first search result causing display of the first electronic content linked to by the first link of the first search result.

1. An electronic search system comprising: at least one processor; and at least one computer-readable storage medium encoded with executable instructions that, when executed by the at least one processor, causes the at least one processor to perform operations comprising: causing display of at least a portion of an interface that includes an input field configured to enable a user to enter input to define a search query; receiving first search input entered in the input field included in the interface; after receiving the first search input entered in the input field included in the interface: accessing a first search query based on the first search input entered in the input field included in the interface; initiating performance of a first search to identify search results that are responsive to the first search query; based on the first search to identify search results that are responsive to the first search query, accessing a first list of search results that are responsive to the first search query, the first list of search results including at least a first search result that is responsive to the first search query and that links to first electronic content; and causing display of the first list of search results accessed based on the first search to identify search results that are responsive to the first search query, the display of the first list of search results having a representation of the first search result that includes description information that is descriptive of the first search result and a first link that links to the first electronic content; after causing display of the first list of search results accessed based on the first search to identify search results that are responsive to the first search query, detecting user input selecting the first search result included in the display of the first list of search results; in response to the detection of user input selecting the first search result included in the display of the first list of search results, automatically, without additional user input after the user input selecting the first search result, including the first search result in a second list of search results that is different from the first list of search results, that, when displayed, includes a reformatted representation of the first search result that has reduced description information of the first search result as compared to the description information included in the representation of the first search result in the display of the first list of search results, and that, when displayed, includes at least one interface control that enables a user to add, to the first search result included in the second list of search results, a comment that is displayed in the second list of search results in association with the reformatted representation of the first search result; and after accessing search results based on a second search to identify search results that are responsive to a second search query that is different than the first search query and that was accessed after automatically including the first search result in the second list of search results, including, in the second list of search results, a second search result identified in the second search such that the second list of search results includes the first search result which is responsive to the first search query and the second search result which is responsive to the second search query.

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1. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving, by a server comprising one or more computers, first endorsement information characterizing a first member's rating of a first local product or service provider, wherein the first member is in a member network and is provided with a financial incentive to endorse the first local product or service provider; receiving, by the server from a second member in the member network, a local search query comprising information identifying one or more items to be found and a geographic locale to be searched; identifying, using a member network engine available to the server, that there is an association between the first member and the second member, wherein the association comprises an explicit relationship between the first member and the second member or a common membership of the first member and the second member in a community of the member network, wherein the first member is explicitly related to at least one other member in the member network; ranking items responsive to the local search query based on a type of the association between the second member and the first member in the member network; and responding, by the server, to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items.

13. The computer storage medium of claim 1 , the operations comprising: receiving from the first member information characterizing the first member's rating of an advertisement, and storing the information characterizing the first member's rating of the advertisement in a member network database.

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12. At least one computer-readable storage medium having encoded thereon processor-executable instructions that, when executed by at least one processor, cause the at least one processor to carry out a method, the method comprising: performing a speech recognition process on a first speech input to determine whether at least a portion of the first speech input potentially matches any of a plurality of voice commands; and when it is determined, based on the speech recognition process, that the at least a portion of the first speech input potentially matches at least a first voice command and a second voice command of the plurality of voice commands, attempting to identify a synonym for at least one word of the first voice command, and when the synonym is identified, prompting a user to provide a second speech input including the synonym if the user intended to invoke the first voice command by speaking the first speech input.

15. The at least one computer-readable storage medium of claim 12 , wherein the method further comprises: when it is determined that the at least a portion of the first speech input potentially matches at least the first voice command and the second voice command, attempting to identify a synonym for the second voice command, and when synonyms are identified for the first voice command and the second voice command, further prompting the user to provide a second speech input including the synonym determined for the second voice command if the user intended to invoke the second voice command by speaking the first speech input.

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26. The method of claim 23 , wherein the advertisement comprises, streaming media.

23. A method of distributing, in a networked environment, an object that represents an advertisement, the method comprising: creating the object to represent the advertisement to be made available for access in the networked environment, the object having metadata which specifies criteria of target recipients of the advertisement; matching the criteria specified in the metadata of the object to users in the networked environment, to find recipients who satisfy the criteria; sending the advertisement represented by the object to the recipients who satisfy the criteria; test-posting multiple versions of the object to represent the advertisement, to compute price-performance attributes of each of the multiple versions.

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11. The method of claim 8 , wherein the generating of the message comprises: for each lexical slot in the plurality of lexical slots: accessing the corpus of source data corresponding to the lexical slot; selecting a term from the corpus of source data in accordance with the grammatical constraint corresponding to the lexical slot; and populating the lexical slot with the selected term.

8. A method comprising: receiving, from a client device, a request to share content on a social network platform; in response to receiving the request, accessing a generative grammar model defining a message structure, the message structure including a plurality of lexical slots, the generative grammar model specifying: a corpus of source data to populate each lexical slot in the plurality of lexical slots; and a a grammatical constraint for each lexical slot in the plurality of lexical slots; generating, by a hardware processor, a message using the generative grammar model; verifying that the message adheres to a messaging standard of the social network platform; and causing the message to be published as an entry on the social network platform.

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5. The method of claim 1 , further comprising: training, by at least one computing device, the content kernel using at least the content feature information associated with each content item of the plurality of content items in the training set; training, by at least one computing device, the semantic kernel using at least the semantic feature information associated with each content item of the plurality of content items in the training set; and training, by at least one computing device, the social kernel using at least the social network feature information associated with each content item of the plurality of content items in the training set.

1. A method comprising: training, by at least one computing device, a machine-modeled kernel jointly modeling content, semantic information and social network information, the kernel for use with a digital content annotation and recommendation system, the training comprising building the kernel using a content kernel trained using a training set comprising content feature information, a semantic kernel trained using semantic feature information of the training data set and a social network kernel trained using social network feature information of the training data set, an implicit social network determined from a plurality of content items is used in determining the social network feature information used in training the kernel; identifying, by the at least one computing device, one or more annotations for a test content item of the content data store other than the plurality of content items used to train the kernel, the identifying using the trained kernel and the test content item's content feature information to identify the one or more annotations; and serving, by the at least one computing device and to a client computing device of a user via an electronic communications network, the test content item based on the one or more identified annotations and an interest of the user, the serving of the test content item to the user computing device resulting in the test content item being output by the user computing device.

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4. The system of claim 3 , wherein said navigation constraint module constrains navigation of the user interface input components by controlling sizes of the components based on probabilities of the components being next selected as determined by employing the plural language models.

3. The system of claim 2 , further comprising a navigation constraint module employing the plural language models, based on previous selections, to constrain navigation of the selectable user interface input components.

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14. The mechanism of claim 13 wherein the group includes a routine for broadcasting events to mobile agent objects associated with the group.

16. The mechanism of claim 14 wherein an event indicating deadlock is broadcast by the group when the group determines that a mobile agent object has entered a collaboration state but has not arrived at the synchronization point.

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18. The method of claim 17 , wherein utilizing a grammar as a basis for identifying an attribute that corresponds to a plurality of system resources comprises utilizing a grammar as a basis for identifying a characteristic of software applications, and wherein the list of the plurality of identified system resources is narrowed by the user based upon a hierarchy.

17. The method of claim 16 , further comprising: executing a user confirmation step prior to executing the function.

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4. The storage medium of claim 1 , wherein selecting the particular extraction module from the plurality of extraction modules for the web page comprises selecting the particular extraction module based on a match between at least a portion of a first universal resource locator for the web page to a second universal resource locator, the second universal resource locator corresponding to a second web page for which print-ready documents were created using the particular extraction module.

1. A non-transitory machine-readable storage medium encoded with instructions executable by a processor of a computing device for providing a print-ready document, the machine-readable storage medium comprising: instructions to receive, from a client device, a request for a print-ready document, the request specifying a web page for which the print-ready document is to be provided; instructions to select a particular extraction module to extract content from electronic documents from a plurality of extraction modules for the web page based on a feedback score for the particular extraction module meeting a threshold feedback score that is derived from prior user feedback received from a plurality of client devices, the prior user feedback indicating a measure of quality of print-ready documents created for the web page using content extracted from the web page by the particular extraction module; and instructions to provide data specifying the particular extraction module to a print service that causes presentation of the print-ready document at the client device, the print-ready document including content extracted from the web page by the particular extraction module.

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8. The method of claim 1 , further comprising: encrypting the new unique nonce using format-preserving encryption; and storing the encrypted new unique nonce.

1. A computer-implemented method for maintaining encrypted search indexes on third party storage systems, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, as part of a plugin of a search engine, a dynamic search index used by the search engine, wherein: the dynamic search index comprises a plurality of data chunks; each of the plurality of data chunks comprises one or more data blocks; each of the plurality of data chunks has been encrypted using a unique nonce; and a search-index initialization vector is designated and stored for encrypting the dynamic search index; and enabling a single data chunk in the plurality of data chunks to be accessed by decrypting, as part of the plugin of the search engine, the single data chunk by: calculating a chunk initialization vector for decrypting the single data chunk by: identifying the unique nonce used to encrypt the single data chunk; and deriving the chunk initialization vector by summing the search-index initialization vector with a product of the unique nonce and a number of the one or more data blocks; and using the chunk initialization vector to decrypt the single data chunk; and reencrypting, as part of the plugin of the search engine after the single data chunk has been accessed, the single data chunk by: calculating a new chunk initialization vector for encrypting the single data chunk such that no two data chunks in the plurality of data chunks have identical initialization vectors by: calculating a new unique nonce for the single data chunk; and deriving the new chunk initialization vector by summing the search-index initialization vector with a product of the new unique nonce and the number of the one or more data blocks; and using the new chunk initialization vector to encrypt the single data chunk.

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13. The non-transitory medium of claim 11 , where the content includes hyper-text markup language (HTML) content that includes, for each of the determined action links, a link to a service corresponding to one of the action links.

11. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more devices, cause the one or more devices to: receive, without further interaction by a user of a client, a request for action links that are to be displayed within a document previously requested and received by the client, determine the action links based on information that identifies one or more action services previously defined by the user and that is previously stored in or by the one or more devices, the one or more action services including at least one of one or more email services or one or more social networking services, and the action links providing an opportunity for the user associated with the client to share the document by using one of the one or more action services; generate content that describes the action links; and provide the content to the client for presentation of the document with the content that describes the action links.

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22. The method of claim 5 comprising measuring the linguistic richness based on a level of linguistic proficiency determined by variety or vocabulary of words, complexity of words, logical relationships or density of individual thoughts per sentence length.

5. A method for determining if an author of a social media interaction is one of a plurality of customers for whom identification information is registered, the method comprising: receiving identification information registered by the author of the social media interaction that is publicly available, wherein the author's received identification information includes a channel-specific identifier associated with a social media channel and the identification information registered for the plurality of customers includes a channel-specific identifier associated with a different communication channel; and determining a final equivalence of whether the author of the social media interaction is one of the plurality of customers using an equivalence relationship comparing the author's and customer's respective identification information and content information describing the content of the author's social media interaction and content information describing the content of the customer's past interactions, wherein a predetermined threshold is set to define a range for the equivalence relationship within which the author and the customer are determined to have the same identity, wherein the predetermined threshold is set in a testing phase to balance maximizing the accuracy and minimizing missed instances of determining authors and customers to be identical that are previously known to be identical, wherein each of the author's and customer's information is represented by a vector with each of the identification information and content information thereof having values in a respective dimension and wherein the author's and customer's information are compared by calculating the vector difference between their representative vectors to measure a similarity between the author's and customer's information and wherein the content information is selected from the group consisting of: linguistic richness, sentiment, tone, opinion, style, vocabulary, average length of sentences, slang and emoticons; and after determining the final equivalence that the author of the social media interaction is the associated one of the plurality of customers, monitoring that author's social media interactions by the contact center for the associated customer.

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2. The method according to claim 1 , wherein defining the knowledge base comprises calculating a parameterized transition matrix defining the viewer's viewing habits, the parameterized transition matrix containing information of program transitions initiated by the viewer, and wherein the row number and the column number of the element represent the first and second states.

4. The method according to claim 2 , further comprising defining the transition matrix as a two-dimensional matrix with transitions from television channels to television channels in temporal form.

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26. The system for processing content of claim 25 , wherein the computing device is further configured to: identify, in the audio narration, a recitation of the at least one original attribute of the selected original object; generate, from the one or more audio clips, a recitation of at least one attribute of the object selected from the source graph; and replace, in the audio narration, the recitation of the at least one original attribute of the selected original object with the generated recitation of the at least one attribute of the selected object selected from the source graph to form a modified audio narration.

25. A system for processing content, the system comprising: a content data store configured to store a plurality of original items of content, each item of original content comprising audio narration and a plurality of original objects, each original object comprising at least one original attribute; a narration data store comprising one or more audio clips; and a computing device in communication with the content data store and the narration data store, the computing device configured to: select an object from a source graph comprising a plurality of objects, the selected object comprising at least one attribute; access an item of original content; select an original object; and replace, in the item of original content, at least one original attribute of the selected original object with at least one attribute of the object selected from the source graph to form an item of modified content.

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20. The system as claimed in claim 16 , wherein enabling a requestor or searching user to provide a service and/or perform a search in response to a service request and/or query based on one or more communication, collaboration, sharing, searching, messaging, responses via one or more applications including email, instant messaging, video, voice, services including communication services, devices including mobile, networks including interne, intranet and technologies including voice enabled, voice to text or text to voice, SMS, MMS, translation system.

16. A system for requesting social services from group of users, the system comprises of: a central server unit; at least one service provider and/or searcher computer system providing a service and/or performing a search in response to a service request and/or query from a requestor or searching user; at least one search system receiving request that the group service providers and/or group searching is required, presenting a list of groups of service providers and/or groups of searchers having human service providers and/or searcher members with domain specific expertise and rating, receiving selection of a desired service and/or search groups, prompting for and receiving an authentication information from the requestor or searching user, validating the authentication information, determining whether the requestor or searching user may submit the service request and/or query to a human service provider and/or searcher member of the related or selected service providers group and/or searcher group or a service provider or searcher who is not the human service provider or searcher member based on the match making, connections and subscriptions, and accepting the request or query from the requestor or searching user; a service providers and searchers group database including a service providers and search service of searchers service profiles, service name, ID, service types, service details, service categories, taxonomy, ontology, keywords, ranking, hit statistics, comments, service data including request and response resources, list and profile details of group members; a user system including at least one requestor or searching user interface using which the required service providers or searchers group is selected, the list of service providers or searchers groups being presented in an order based at least in part on the ranking of the service providers or searchers groups; a service providers or searchers of groups database including a service provider or searcher profile(s) including name, location, language, resume, qualification, background, experience, identity data, group identity data, authentication information, user data, ranking hit statistics; and an authorized requestors or searching users or registered subscribers database including the service providers or searchers group identity, an authorized user identity and authentication information, and where at least one of the human service provider or searcher members is selected to provide service or perform the search in response to the request or query from the requester or searching user based on a combination of a categories or keywords of the service or search, two way match making preferences, connections and subscriptions.

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7. The apparatus according to claim 5 , wherein the search unit further comprises a search query creation unit configured to create a search query for a keyword of the keyword candidates based on at least one of a descriptive phrase describing the keyword and extracted from the text data by the supplementary information extraction unit, a document structure of the text data containing the keyword, or a document type of the text data containing the keyword.

5. The apparatus according to claim 1 , further comprising: a supplementary information extraction unit configured to extract supplementary information of the keyword candidates by at least extraction of the descriptive phrases describing the keyword candidates from the text data, determination of document structures of the text data containing the keyword candidates, or determination of document types of the text data containing the keyword candidates.

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6. The method of claim 5 wherein generating a first set of tokens from the first portion of the information content using the abstract data structure comprises: finding a token candidate in the first portion of the information content using a token delimiter indicator from a corresponding token identified in the abstract data structure; generating a signature of the token candidate; comparing the signature of the token candidate with a signature of the corresponding token from the abstract data structure; and adding the token candidate to the first set of tokens if the signature of the token candidate matches the signature of the corresponding token from the abstract data structure.

5. The method of claim 4 wherein: the abstract data structure is created to provide an index of the source data, the index comprising signatures of data fragments within the source data; and creating the abstract data structure comprises identifying a plurality of tokens within the source data based on the tabular format, for each token in a word-based language, creating a signature of a relevant token, and adding the signature to the abstract data structure, and for each token in the character-based language, creating a token delimiter indicator and a signature of a relevant token, and adding the token delimiter indicator and the signature to the abstract data structure.

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27. The system of claim 13 , wherein the categories from the categorization tool and the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools to a user on a visual display.

13. A system comprising: a core server computer executing at least one software module comprising: code capable of understanding the format of data provided by a transformation tool; code to convert the data provided by a transformation tool to a data format that maps to a data capture schema, the data capture schema comprising a set of tables to store a copy of unstructured data and attributes of the unstructured data; code to send the copy of the unstructured data to one or more transformation tools; code to parse, via a natural-language processing transformation tool, the copy of the unstructured data to extract sentences from the copy of the unstructured data and then further extract from the extracted sentences sentence-level natural-language processed entities, wherein the sentence-level natural-language processed entities are at least noun phrases; code to extract, via a linguistic processing transformation tool, sentence-level linguistically-processed relationships, wherein the sentence-level linguistically-processed relationships comprise associations between the sentence-level natural-language processed entities; code to send the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools to a categorization tool; wherein the categorization tool determines categorization data elements present in each extracted sentence, wherein the categorization data elements are based on the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships, and are placed within predetermined categories, and a confidence level for each categorization data element, wherein the confidence level for each categorization data element combines one or more data points linked to the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships to create a statistically-oriented calculation of confidence assigned to the categorization data element; code to write the categorization data elements from the categorization tool and the sentence-level natural-language processed entities and the sentence-level linguistically-processed relationships from the one or more transformation tools in a structured database schema; code to output the confidence level for at least one of the categorization data elements for use in structured data tools; wherein each of a plurality of source documents are assigned a unique key that identifies an individual source document throughout a software system allowing (i) cross-analysis, (ii) linking of results for further analysis, (iii) drill-down from analytical reports back to the source document or (iv) drill-down from analytical reports back to transformation information stored in the data capture schema; and wherein the one or more data points are selected from the group consisting of: confidence score of value provided by the one or more transformation tools, number of relationships found in the source of unstructured data compared to the size of the source of unstructured data, average number of relationships per kilobyte for relationships of the same type as a selected relationship, number of entities found to be associated with a relationship compared to an average number of entities for relationships in a same hierarchy, number of times similar relationships have been found in the past, number of entities that are grouped together to form a master entity, a number of times an entity occurred in the source of unstructured data compared to the average number of occurrences for entities in the same hierarchy, weighted confidences based on hierarchy of a relationship or entity, measures of data extraction confidence integrated with the system via an analysis schema, measures based on a fullness of a relationship's attributes, measures based on the confluence of a same finding by multiple transformation tools, measures based on the source of the unstructured data, and combinations thereof.

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6. The attribute-assigning image-processing system of claim 1 wherein the set of second-level feature detectors includes a number a of feature detectors, where a is greater than 2, that each generates a feature detector for each of b normalized regions, where b is greater than or equal to 5, resulting in generation of ab feature vectors that are distributed among the attribute classifiers.

1. An attribute-assigning image-processing system comprising: a distributed computing system that includes multiple computer systems, each having one or more processors, one or more memories, one or more mass-storage devices, and one or more network interconnections; an input-image memory for receiving an input image provided by one or more of the multiple computer systems; a set of first-level feature detectors, provided by one or more of the multiple computer systems, that detect face-containing subimages within the input image and, for each face-containing subimage, generate a set of normalized regions; a set of second-level feature detectors that generate a set of feature vectors from each normalized region; a set of attribute classifiers that each outputs an attribute value and an associated probability that reflects a likelihood that the attribute value returned in response to input of one or more feature vectors reflects the attribute value that would be assigned to the image of the facial feature contained in the normalized region from which the set of second-level feature detectors produced the input feature vectors; and a controller that submits the input image to the first-level feature detectors in order to generate sets of normalized regions for each face-containing subimage in the input image; submits each set of normalized regions to generate a set of feature vectors; and submits subsets of feature vectors to each attribute classifier in an ordered list of attribute classifiers to assign attributes to each face-containing subimage.

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1. A computer-implemented method comprising: registering a sponsored concept from a sponsoring company; receiving, at a server computer via a data network, the sponsored concept submitted by the sponsoring company, the sponsored concept indicating particular subject matter about which the sponsoring company would like to converse; receiving a first topic of interest submitted by a first user in a search query, the first topic of interest indicating particular subject matter about which the first user would like to converse; determining, by use of a data processor and prior to establishing a conversation, if the sponsored concept and the first topic of interest fit within match criteria by comparing the sponsored concept with the first topic of interest; generating for the first user, by use of the data processor, if the sponsored concept and the first topic of interest fit within match criteria, a link enabling the first user to establish a conversation between the first user and an agent of the sponsoring company, the link being a user interface element that can be activated by the first user; upon activation of the link, receiving a request from a computing system of the first user to establish the conversation; using a connection path associated with a computing system of the agent to establish the conversation between the first user and the agent of the sponsoring company.

12. The computer-implemented method as claimed in claim 1 including displaying a user interface component on a display device of the agent of the sponsoring company and displaying a user interface component on a display device of the first user after establishing the conversation upon activation of the link.

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16. The method of claim 14 , wherein when the custom text-to-speech voice does not conform to the selected synthesis quality, recording one of additional words and additional phrases to increase the in-domain inventory of synthesis speech units.

14. The method of claim 13 , further comprising: determining whether the custom text-to-speech voice conforms to a selected synthesis quality.

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1. A method of determining dependencies between elements of a computing software package based on a dictionary using one or more processors of a processor-based system, the method comprising: receiving an operation indicator that specifies that an operation is to be performed on a first element of a plurality of elements that are defined by a plurality of respective files that are included in the computing software package; generating, using at least one of the one or more processors, the dictionary that is stored on a computer database and that includes a plurality of indexes each of which has one or more values, at least one index of the plurality of indexes having a plurality of values, the plurality of indexes corresponding to a plurality of respective resources each of which is producible by at least one element of the plurality of elements that are defined by the plurality of respective files that are included in the computing software package, each value specifying an element of the plurality of elements that produces the resource that corresponds to the respective index; receiving a resource consumption indicator that specifies a designated resource of the plurality of resources that the first element consumes; comparing the resource consumption indicator to the plurality of indexes to match the resource consumption indicator to an index of the plurality of indexes that corresponds to the designated resource; and determining that the first element depends on a second element that produces the designated resource based on the index that corresponds to the designated resource having a value that specifies that the second element produces the designated resource.

2. The method of claim 1 , wherein a first index of the plurality of indexes has a first plurality of values; wherein comparing the resource consumption indicator to the plurality of indexes comprises: comparing the resource consumption indicator to the plurality of indexes to match the resource consumption indicator to the first index which corresponds to the designated resource; and wherein determining that the first element depends on the second element comprises: determining that the first element depends on a plurality of second elements that produce the designated resource based on the first index having the first plurality of values that specify that the plurality of respective second elements produce the designated resource.

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17. An apparatus for managing components of an application enablement suite (AES), comprising: a workflow designer engine server including a workflow designer engine module; and a developer portal server including a developer portal module in operative communication with the workflow designer engine module, wherein the workflow designer engine module and developer portal module are configured to communicate with an AES; wherein the developer portal module is configured to provide an application developer with access to the workflow designer engine module in response to a proper authentication sequence, wherein the authentication sequence is initiated in response to the application developer activating the workflow designer engine module via a user device in operative communication with the developer portal module; wherein the workflow designer engine module is configured to activate a composite network application manager in response to the application developer selecting a manage composite network application function via the user device in conjunction with a graphical user interface (GUI) controlled by the developer portal module; wherein the workflow designer engine module and developer portal module are configured to create a new composite network application using archetypes of the workflow designer engine module and repositories in storage devices of the developer portal module in response to the application developer defining at least some parameters for the new composite network application in conjunction with the GUI, wherein the new composite network application is associated with a new or existing composite network service available to subscribers via the AES and associated with at least one of multiple network services, multiple service providers, multiple service networks, and multiple communication sessions; wherein the workflow designer engine module is configured to activate an application program interface (API) manager in response to the application developer selecting a manage API function via the user device in conjunction with the GUI; wherein the workflow designer engine module and developer portal module are configured to create a new API using archetypes of the workflow designer engine module and repositories in storage devices of the developer portal module in response to the application developer defining at least some parameters for the new API in conjunction with the GUI, wherein the new API is associated with the new composite network application; wherein the workflow designer engine and developer portal are configured to form a layer between the GUI and the AES; wherein the archetypes include a configurable set of basic definitions and design patterns accessible to the application developer via the developer portal for creation of the new network application; wherein the repositories include a configurable set of application features accessible to the application developer via the developer portal for creation of the new network application.

21. The apparatus set forth in claim 17 wherein the workflow designer engine module is configured to activate a development tool manager in response to selection of a manage development tool function via the GUI; and wherein the workflow designer engine module and developer portal module are configured to create a new simulator for testing the new composite network application using archetypes of the workflow designer engine and repositories of the developer portal based at least in part on test processes and parameters for the new simulator identified via the GUI, wherein the new simulator is adapted for testing the new composite network application in conjunction with repositories of the developer portal to verify that the new composite network application is capable of providing the new or existing composite network service to subscribers via the AES.

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1. A computer-implemented optimization method for instance-based sentence boundary determination comprising the steps of: setting by a computer an initial upper bound (UB) of a cost associated with an optimized solution to a lowest cost derived by several greedy algorithms; identifying by the computer all corpus instances stored in an electronic database that contains one or more of a plurality of desired propositions; forming by the computer a search tree structure with branches for each of plurality of identified corpus instances that contain one or more of said plurality of desired propositions; deleting by the computer one or more of a plurality of undesired propositions from said identified corpus instances; updating by the computer an overall cost with one or more deletion costs; inserting by the computer one or more of said plurality of desired propositions that were not contained in said corpus instance into said corpus instance; updating by the computer the overall cost with one or more insertion costs; calculating by the computer a lower bound (LB) of a cost associated with a current solution or partial solution; pruning by the computer a current search branch if the LB is greater than the UB; recursively computing by the computer a best solution associated with generating one or more additional sentences to convey the rest of said plurality of desired propositions that were not contained in said corpus instance; updating by the computer the overall cost with a boundary cost plus a cost associated with the best solution found by the recursively computing procedure; updating by the computer UB if the current overall cost is lower than UB; and outputting by the computer a solution that has the lowest overall cost using a set of said identified corpus instances with a set of said deletion, insertion and sentence break operations.

8. The method of claim 1 further comprising the step of re-calculating said insertion costs, said deletion costs and said sentence boundary costs with a overall cost of Cost( P )=Cost d ( C i ,D )+Cost i ( E )+ SBC +Cost( Q ) wherein, a set of variables of said set of relationship includes: P is a set of propositions to be conveyed, C i is one of the instances within the corpus identified to convey P, D is a set of propositions to be deleted from C i , I is a set of propositions to be added, E is a subset of I to be inserted in C i , Q is the rest of propositions in I that will be realized in one or more different sentences (Q=I−E), and SBC is a sentence boundary cost of a natural language generator (NLG).

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11. The system according to claim 10 , wherein the functions further comprise, before applying the editing: locating the text now loaded into the textbox to which the editing operation is directed; placing an operator on the text to which the editing operation is directed; and receiving an operation command of the editing operation, the command comprising at least one operation of viewing, inserting, deleting, and modifying.

10. The system according to claim 8 , wherein the functions further comprise: in response to monitoring an event of an editing operation directed to the overflowed text in the extended window, performing, without a user request: loading the overflowed text to be edited from the extended window into the textbox, thereby causing a new overflow of the length of the textbox; determining newly-overflowed text as text which has been entered but is not currently displayed in the textbox due to the new overflow; displaying the newly-overflowed text in the extended window; and applying the editing operation to the text now loaded into the textbox.

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3. The method of claim 2 wherein, upon said target person answering said telephone call, said method further comprises initiating a speech recognition application with said target person.

2. The method of claim 1 wherein, in step F, if said speech recognition analysis determines that said spoken response indicates that said answering person is not said target person, a next step comprises initiating a prerecorded query asking for said target person.

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13. A method comprising: receiving a query that involves a database operation and one or more other operations; in response to receiving the query: processing, by a microprocessor, the one or more other operations; sending, to a coprocessor that is different than the microprocessor, a database operation command that corresponds to the database operation and that is associated with one or more values; processing, by the coprocessor, the database operation command by: performing a comparison between input data that is referenced by the query and the one or more values that are associated with the database operation command; generating result data based on the comparison; causing the result data to be stored.

26. The method of claim 13 , wherein generating the result data based on the comparison comprises generating a bit vector, wherein each bit in the bit vector indicates whether a comparison yielded a true or false.

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12. The multi-tenant computing platform of claim 10 , further comprising a note board application configured to display one or more notes without respectively associated records.

10. A multi-tenant computing platform, comprising: a records application configured to store records in a tenant data store; each record having record data stored therein; a graphical user interface configured to display a graphical representation of data associated with one or more records such that the display is restricted to a first set of one or more credentialed users; and a notes application configured to facilitate generation of a note associated with one or more records in the tenant data store, each note having restricted access such that only a second set of one or more credentialed users may access the note, the second set different from the first set; wherein the graphical user interface is configured to display a note over a record if and only if a credentialed user of the graphical user interface is in the first set of one or more credentialed users and in the second set of one or more credentialed users.

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9. The method of claim 1 , wherein the query data is transmitted over the network using an Internet-based protocol.

1. A distributed method of recognizing and responding in real time to a user question posed within an application program executing on a client device, comprising: receiving query data generated by the client device over a network; considering a context experienced by a user within the application and loading one or both of appropriate grammars or dictionaries for the context; processing the query data at a server device to form a query text associated with the user question using the appropriate grammars and dictionaries; submitting the query text to a database query engine and a natural language engine; processing the query text using the natural language engine to identify any word phrases in the query text; retrieving a first set of question/answer pairs from a question/answer pair database using the database query engine; forming a combined query to a question/answer pair database using the database query engine, the combined query being based on the query text concatenated with the word phrases and retrieving a second set of question/answer pairs using the combined query; evaluating the first and second sets of question/answer pairs by comparing word phrases in the sets of question/answer pairs with the word phrases from the query text to identify at least one question/answer pair that best matches the user question; and providing an answer to the user question in real-time over a distributed query system, the answer being determined from the question/answer pair that best matches the user question.

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6. A computer program product comprising: one or more computer readable storage media and program instructions stored on said one or more computer readable storage media, said program instructions comprising instructions to: receive a question, said question being directed to a domain-specific question answering system, wherein said question is requesting at least two distinct pieces of information; extract two or more distinct queries from said question, based on a query decomposing rule library by comparing said question to said query decomposing rule library to identify a matching decomposition rule, wherein said comparing includes using an index scan, using a keyword scan, parsing said query decomposing rule library, and using a segment scan, wherein said query decomposing rule library includes combinations of semantic, syntactic, grammatical, structural, and other predetermined rules for identifying distinct queries within said question; generate two or more question sets, each of said two or more question sets addressing all of said two or more queries, wherein said generated two or more questions sets are expressed in a language and format that said question answering system can interpret and process, wherein both said first question set and said second question set include at least one question for each of said two or more queries extracted from said question, and wherein said second question set includes at least one question different from said first question set; select one of said two or more question sets to yield a selected question set, based on analyzing each of said two or more question sets according to a pre-trained model, wherein said pre-trained model is a term vector model, wherein said term vector model is an algebraic model for representing elements within a text document as vectors and generates a number of dimensions based on keywords, terms, and elements within said extracted queries, wherein said two or more question sets are selected based on a first optimal score, wherein said first optimal score is based a number of specific terms and irrelevant terms in questions in each of said two or more question sets, and wherein said irrelevant terms lower said first optimal score; present said selected question set to said question answering system and a user; determine at least one answer set for said selected question set by accessing a structured repository of information using said pre-trained model; and present said answer set to said question answering system.

8. The computer program product of claim 6 , wherein instructions to extract two or more queries from said question comprises instructions to: compare said question against the query decomposing rule library to yield one or more matching query decomposing rules; and apply said one or more matching query decomposing rules to said question to yield said two or more queries.

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11. The computer-implemented method of claim 10 , further comprising determining when a reading of a first phonetic symbol is similar to a reading of a second phonetic symbol and when the readings are similar; mapping the first phonetic symbol and the second phonetic symbol to the same key.

12. The computer-implemented method of claim 11 , wherein the number of keys is less than forty two.

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7. The system as recited in claim 6 , wherein the control instructions correspond to a test grammar.

8. The system as recited in claim 7 wherein the test case generation component is further operative to generate the second set of test cases from the test grammar.

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2. The method of claim 1 , wherein the plurality of iterations are performed until the estimated revised scores of the unscored actions stabilize.

1. A computer implemented method comprising: receiving a set of actions indicating interaction with web content, the set of actions including scored and unscored actions where a scored action is associated with a known score of at least one property of a user associated with the action; inferring initial scores for the web content based on the known scores of the scored actions; estimating initial scores for the unscored actions; inferring revised scores for the web content and inferring initial scores for the web content only associated with the unscored actions based on the known scores of the scored actions and the initial scores of the unscored actions; estimating, by one or more processors, revised scores for the unscored actions based on the revised scores for the web content associated with the scored actions and the initial scores for the web content only associated with the unscored actions; inferring, by the one or more processors, revised scores for at least a portion of the web content based on the known scores of the scored actions and the revised scores of the unscored actions; and performing a plurality of iterations of the estimating and inferring steps above.

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5. The method as claimed in claim 4 , wherein said at least one feature is one or more features chosen from a group of features consisting of a keyword pattern, a part of speech pattern, a concept pattern, and a word string similarity.

4. The method as claimed in claim 1 , wherein the discovering the one or more homonyms synonyms of the at least a monitored vocabulary set is through the previous and the next feature windows of each monitored vocabulary of said at least a monitored vocabulary set to capture at least one feature, to determine whether one or more new words of the plurality of new added data belong to at least one homonym synonym of said monitored vocabulary.

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21. A method in accordance with claim 20 , wherein said step of managing access to said instance data comprises authenticating users through several levels of authentication describing user rights.

20. A method for managing instance data, comprising: defining a metadata model establishing metadata elements and a table driven infrastructure for storing the instance data, said instance data organized according to said metadata model; storing said metadata and said instance data in a relational database, altering said metadata model when necessary without requiring reorganization or substantial manipulation of said instance data, creating a user interface, managing access to said instance data by users based on a security scheme, said managing including allowing authorized users to modify said instance data using a computer through said user interface.

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14. The apparatus of claim 11 , in which the at least one processor is further configured: to refine the search terms based at least in part on the executed query, and to monitor for matches to a refined query.

11. The apparatus of claim 10 , in which the at least one processor is further configured: to analyze the extracted data; and to receive feedback from the user based at least in part on the established communication channel.

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1. An information processing apparatus comprising: a display unit configured to display a first screen that displays content acquired from an external server and a second screen that displays content stored in the information processing apparatus; an accepting unit configured to accept, from a user via the first screen, a selection of a language to be used to display the first screen; a requesting unit configured to request, from the external server, content corresponding to the selected language; a first determination unit configured to determine whether the external server, of which the requesting unit makes the request, is a specific external server; and a setting unit configured to, when said first determination unit determines that the external server, of which the requesting unit makes the request, is the specific external server, set a language to be used to display the second screen to the same language as the selected language.

4. The apparatus according to claim 1 , wherein the first screen is an operation screen to be used to operate an application provided in the external server, and the second screen is an operation screen to be used to operate an application provided in the information processing apparatus.

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12. Apparatus for the recognition of speech, of the type claimed in claim 11, said apparatus being further characterized in that the model storing means includes means for storing an ergodic model in which any state can occur after any other state.

14. Apparatus for the recognition of speech, of the type claimed in claim 12, said apparatus being further characterized in that the aligning means evaluates said multiple proposed lexical candidates to select only the best one, whereby the aligning means is capable of producing a selection signal representing the utterance as a word.

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1. An editable information management method comprising: storing editable information as a master file and a plurality of segment files, each segment file being editable independently of other segment files; combining said master file and said segment files in a manner specified by said master file to create said editable information; displaying said editable information for editing using an application program, said application program comprising an add in configured to combine said segment objects; receiving edit instructions to edit part of the displayed editable information corresponding to a predetermined segment file; and updating said predetermined segment file in response to said editing.

19. A method according to claim 1 , wherein at least one of said segment files is associated with a plurality of master files.

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1. A method, performed using at least one computing device, for identifying a set of resources associated with respective domains, comprising: providing context information that pertains to interaction, by a user, with a user device, the context information including textual information associated with content presented to the user by the user device; providing, for each of a plurality of individual domains, individual-domain score information that indicates relevance of the context information to a corresponding individual domain, plural instances of the individual-domain score information comprising plural-domain score information, the providing including (i) receiving data from an entity associated with corresponding individual domain, the data characterizing at least goods or services of the entity, and (ii) generating a language model that identities characteristics of the entity, based on the received data; and identifying a set of resources based on the plural-domain score information for presentation to the user, the set of resources assisting the user in performing an action within a task having plural parts.

9. The method of claim 1 , wherein said identifying of the set of resources comprises ranking resources based on the plural-domain score information.

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15. The method of claim 11 , further comprising: after said anchor is built, categorizing said chat data into said team/department names.

11. The method of claim 9 , further comprising: after said anchor is built, using positive hits generated during anchor building in connection with edit-distance to obtain a temporary categorization of a team/department.

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1. A system, comprising: one or more computer devices configured to implement a web services platform configured to provide a web service interface to a searchable data service, wherein the web services platform is configured to receive service requests from a plurality of client applications in accordance with the web service interface, wherein the service requests comprise query requests and storage requests, and wherein the web service interface provides a common message endpoint to the plurality of client applications to send the query requests and storage requests; and a plurality of computer devices configured to implement a plurality of nodes configured to participate in the searchable data service to: store searchable data service objects specified in received storage requests in respective searchable indexes for a plurality of independent data stores used by the client applications, wherein the searchable indexes are on the plurality of nodes, wherein the data stores are on one or more storage devices each on a network and separate from the one or more computer devices that implement the plurality of nodes configured to participate in the searchable data service, wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores, wherein each searchable data service object specifies two or more attributes of a particular entity in a particular data store, wherein the attributes include a unique entity identifier for locating the particular entity in the particular data store; locate sets of one or more searchable data service objects from the searchable indexes that satisfy received query requests, wherein the received query requests specify one of the searchable indexes; and return at least the entity identifiers from the sets of one or more searchable data service objects that satisfy the query requests to the client applications in accordance with the web service interface.

28. The system as recited in claim 1 , wherein the plurality of nodes comprises a plurality of storage nodes, wherein the plurality of storage nodes is distributed among two or more data centers, wherein each data center comprises two or more of the plurality of storage nodes; wherein at least two of the storage nodes in a data center persistently store replicas of a partition of a particular searchable index; and wherein at least two other storage nodes in at least one other data center persistently store replicas of the partition of the particular searchable index.

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7. The method of claim 1 , wherein the certain operations comprise a fourth set of one or more operations that are to be performed on a second data source; and wherein the method further comprises: determining that a second server associated with the second data source is capable of performing the fourth set of one or more operations; sending a second request to the second server to perform the fourth set of one or more operations; receiving a second response to the second request, wherein the second response comprises results of performing the fourth set of one or more operations on the second data source; and wherein the generating step comprises generating results for the query based at least in part on the results of performing the first set of one or more operations and the results of performing the fourth set of one or more operations.

1. A method of processing a query, comprising the computer-implemented steps of: receiving the query, wherein the query specifies certain operations to be performed, wherein the certain operations comprise a first set of one or more operations that are to be performed on a markup language data source; wherein the first set of one or more operations includes a second set of one or more operations; determining that the first set of one or more operations can be performed at any one of a plurality of entities; wherein the plurality of entities includes one or more of an XML database server, a relational database server, and a middle-tier engine; generating a plurality of execution plans for executing the query, wherein the plurality of execution plans include: a first execution plan indicating a first entity at which the second set of one or more operations are to be performed; and a second execution plan indicating a second entity at which the second set of one or more operations are to be performed; selecting, based on a particular set of criteria, a particular execution plan from the plurality of execution plans; wherein selecting the particular execution plan from the plurality of execution plans comprises one or more of: selecting the particular execution plan based at least in part on costs determined for the plurality of execution plans; and selecting the particular execution plan by using one or more rules to determine which execution plan, of the plurality of execution plans, to use for executing the query; wherein the selected particular execution plan indicates a first server at which the second set of one or more operations are to be performed; determining that a third set of one or more operations are to be performed at the middle-tier engine, wherein the first set of one or more operations include all operations in the third set of one or more operations, and the third set of one or more operations include no operation that are in the second set of one or more operations; sending a request to the first server to perform the second set of one or more operations; receiving a response to the request, wherein the response contains results of performing the second set of one or more operations on the markup language data source; and generating results for the query based at least in part on the results of performing the second set of one or more operations; wherein the steps of generating the plurality of execution plans and selecting the particular execution plan are performed by one or more computing devices.

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14. The computer program product of claim 8 , wherein data that fails all such threshold comparisons is discarded by the modified classifier.

8. A computer program product for configuring a classifier structure, the computer program product comprising a computer readable storage medium not including propagated signals having program code embodied therewith, the program code executable by a processor to: receive a classifier structure for identifying one or more features of input data, the structure having a parent classifier trained as a binary classifier and a plurality of child binary classifiers, wherein the parent classifier is configured to identify one feature of interest by determining a numeric score representing a measure of a likelihood of the input data including the feature of interest; add a plurality of thresholds to the parent classifier to generate a modified classifier, wherein each threshold is associated with a different child binary classifier and the plurality of thresholds control how data is distributed by the parent modified classifier to the child binary classifiers, wherein each threshold has a respective cost; and set the plurality of thresholds to values different from one another to minimize the total cost based on the resources available to the child binary classifiers, wherein the modified classifier is configured to output data to each child binary classifier by comparing the determined score against the threshold associated with the corresponding child classifier, wherein the modified classifier includes at least two output branches for either outputting data excluding the feature or data including the feature to two child binary classifiers in parallel.

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1. A multimodal system for receiving inputs via more than one mode from a user and for interpretation and display of text based upon the inputs received via the more than one modes, the system comprising: a) a user input device having a plurality of modes, one mode accepting speech input and the remaining modes accepting entry of non-speech input; b) a memory containing a plurality of acoustic networks, each of the plurality of acoustic networks being associated with at least one mode; and c) a processor to: i) process the speech input and at least one non-speech input accepted by at least one of the remaining modes; ii) dynamically adapting an acoustic network based on the speech input and the at least one non-speech input; iii) perform automatic speech recognition using the dynamically adapted acoustic network; iv) determine an output based on the automatic speech recognition; and v) return the output to aid in a determination of a subsequent user-action.

12. The system of claim 1 , wherein the system is selectively configured to receive speech input after receiving at least one non-speech input.

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15. The computer system of claim 13 , wherein the responding step further includes program instructions, stored on the one or more computer readable storage media, which when executed by a processor, cause the processor to determine if the portion of the textual content of the phrase present in the phrase dictionary does not exceed a threshold, wherein the threshold is a total number of words.

13. A computer system managing textual content of phrases, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored on the one or more computer readable storage media, for execution by at least one of the one or more computer processors, the program instructions comprising: program instructions to determine if a phrase is entered into a first field in a display, wherein the phrase contains textual content; program instructions to determine a user name associated with the phrase entered into the first field of the display; program instructions to query a directory for information associated with the determined user name, wherein the information includes at least a list of titles and associated responsibilities of the determined user name; program instructions to determine if a portion of the textual content of the phrase is present in a phrase dictionary, wherein the phrase dictionary contains textual content of one or more topics; and program instructions to, responsive to determining that the portion of the textual content of the phrase is not present in the phrase dictionary, determine to not enter the portion of the textual content of the phrase in a second field of the display.

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14. A non-transitory computer-readable medium having a plurality of computer-executable instructions stored thereon, the non-transitory computer-readable medium comprising: instructions for receiving a request from an interface associated with a client device for a web page created in a specific language, the web page comprising content in the specific language, one or more elements in a first markup language used by an interface of the client device to display the content, and one or more one or elements in a second markup language, the second markup language being an intermediate non-scripting language different from the first language; instructions for extracting a locale-specific preference from a header in the request, the locale-specific preference in the header further including one or more entries that each indicate a preference level for document languages; instructions for selecting a locale-specific module corresponding to the locale-specific module corresponding to the locale-specific preference, the selected locale-specific module built in a language supported by a script associated with the requested web page using one or more user-supplied definitions associating an element of the webpage in the second markup language with one or more locale-specific formattings; instructions for sending the locale-specific module to the client device for storage at the client device; and instructions for sending the requested web page to the client device for storage at the client device, wherein, when the client device encounters the element of the web page in the second markup language when executing the script, the client device uses the locale specific module to determine the one or more locale-specific formattings.

18. The non-transitory computer-readable medium of claim 14 , wherein the instructions for selecting the locale-specific preference for the interface associated with the client from the request comprise: instructions for determining whether a locale-specific module in a plurality of locale-specific modules matches the locale-specific preference; instructions for, if a match is not found, determining a locale-specific module that substantially matches the locale-specific preference in the plurality of locale-specific modules; and instructions for, if a locale-specific module that substantially matches the locale-specific preference is not found, determining a default locale-specific module.

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1. A method comprising: monitoring a social networking system for actions associated with users connected to a target user; identifying an action associated with a user connected to the target user; determining the relevance of the identified action to the target user; responsive to the determined relevance exceeding a pre-determined threshold: displaying the identified action and the identity of the connected user as a feed story in a newsfeed interface, the feed story comprising the identified action, the identity of the connected user, and information related to the context of the identified action and the connected user; and displaying the identified action and the connected user as a ticker story in a news ticker interface, the ticker story comprising the identified action and the identity of the connected user; and responsive to the determined relevance failing to exceed the pre-determined threshold: displaying the identified action and the connected user as a ticker story in a news ticker interface, the ticker story comprising the identified action and the identity of the connected user.

7. The method of claim 1 , wherein the news ticker interface is adjacent to the newsfeed interface.

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4. A system supporting speech recognition comprising: two or more clients, each client comprising the capability to receive audio speech from a user, store the audio speech in one or more buffers, each buffer comprising a portion of the received audio speech, encode a buffer of the received audio speech before all of the audio speech is received, package the encoded buffer to receive audio speech into one or more packets to be transmitted over the Internet before all of the audio speech is received, and transmit a packet of encoded audio speech over the Internet before all of the audio speech is received; and a server, the server comprising the capability to receive packets of encoded audio speech from at least two clients, decode each of the packets of audio speech and store the resultant raw speech into one or more buffers for the respective client, and evaluate the resultant raw speech received from each of the at least two clients, wherein the server further comprises the capability to transmit a response to a client, the response a result of the server's evaluation of the resultant raw speech received from the client, a client of the two or more clients further comprises the capability to receive the response from the server, the response is in text format, and a client of the two or more clients comprises a text-to-speech engine which converts the text format response to audio data, and an audio output device that the client uses to output the audio data to a user, and a processing time used to evaluate the resultant raw speech will vary based on a value communicated to the server from a client.

5. The system of claim 4 wherein the value communicated to the server from a client is a user objective, a user selects the user objective at a client, the client transmits the user objective to the server, and the server evaluates the resultant raw speech received from the client based on the user objective.

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17. The method of claim 15 , further comprising: synchronizing the animation of one or more features of the avatar with delivery to the recipient of stimulation signals representative of the received speech signals.

15. A method, comprising: determining a degree of tonal deafness of a recipient of an implantable auditory prosthesis, wherein the implantable auditory prosthesis is configured to operate with an external device configured to display a graphical representation that enables the recipient to compensate for tonal deafness associated with delivery of stimulation signals to the recipient; and based on the degree of the tonal deafness of the recipient, setting a predetermined display mode for the graphical representation in which the external device displays a humanoid avatar that includes at least a head that includes a mouth region; and animating the mouth region of the avatar based on the received speech signals so as to emulate vocal articulator movements of a speaker of the received speech signals.

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12. The menu management system of claim 10 wherein said list menu is compatible with at least one computer operating system.

10. A computer software menu management system consisting of, storing a keyword in a controlled vocabulary and its predetermined code in a database that links each said keyword to a parent keyword at the parent level thereby creating a hierarchical organization having a plurality of levels, selecting a set of keywords from said database that are all linked to the same said parent keyword and are located at an identical level in said hierarchical organization, generating a list menu based on said set of keywords, adding a navigation control to said menu system, adding a search control to said menu system, displaying said list menu, fetching a selection made by an end-user associated with said navigation control, with said search control, and with said set of keywords in said list menu, generating another said list menu representing a parent and a child level in said hierarchical organization depending upon the hype of navigation control selected by said end-user. fetching at least one said keyword selected by said end-user from said list menu selected when said search control is selected by said end-user, generating a database query that includes at least one said keyword selected by said end-user in said list menu when said search control is selected by said end-user.

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9. The computer implemented method of claim 8 , wherein distinguishing a value from other values comprises one of highlighting the value or displaying a marker adjacent to the value.

8. The computer implemented method of claim 1 , wherein the first value is distinguished from remaining values of the first plurality of values and the second value is distinguished from remaining values of the second plurality of values.

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11. A method for connecting words, phrases, or symbols within the content of a transmitted data to telecommunication codes, comprising: selecting a group of Telecom Codes, each of which is characterized with a first part as a directly dialed Head Code and a second part as a Sub Code that contains extra digits of Arabic numbers following an original Head Code, wherein each Sub Code within the selected group Telecom Codes is at least one of non-ambiguous, unique, or same set of numbers as numbers from other groups of Sub Codes or be connected to them, wherein the selected group of Telecom Codes is configured in a database, whereby any digits of Telecom Code in the selected group or any other groups axe any characters permitted by telecom network systems; defining a unique format or form of at least one of selected words, phrases, or symbols in a plurality of languages, any multimedia expressions as at least one Content Name, wherein the at least one Content Name is located in any place within the transmitted data, wherein the defined Content Name is configured in the database; assigning at least one Content Name to at least one Telecom Code, wherein connection relations and rules of directing between them are characterized as valid and executable on at least one-to-one basis, wherein each of the connection relations and the rules of-directing is configured in the database; and utilizing one or more logic structures or computing programs within a computerized system to manage at least one of the Telecom Code, Content Name, connecting/directing function, receiving/analyzing the content transmitted, detecting existence of any specific Content Name, and redirecting the transmitted content to the connected Telecom Codes.

13. The method of claim 11 , wherein Sub Code or connected Telecom Code comprise at least one of any cell phone number and the same set of Arabic number assigned to other hardware terminals for end user.

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11. A computer system, said computer system comprising a computer, said computer configured to perform a method for improving satisfaction of a user at a user machine, said method comprising: said computer prompting a user at the user machine to select a language usage pattern preference from a plurality of language usage pattern preference choices respectively comprising a plurality of text passages, each text passage expressing different text; after said prompting, said computer receiving from the user machine a language usage pattern preference selected by the user from the plurality of language usage pattern preference choices; and said computer storing, in a user profile of the user located in a database accessible to the computer, a flag indicative of the selected language usage pattern preference.

12. The computer system of claim 11 , wherein each text passage comprises a different one or more personal pronouns not comprised by any other text passage of the plurality of text passages.

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9. The system of claim 1 , wherein an order of processing of the runtime solution can be further adjusted and controlled through both human control as well as through machine learning methods.

1. A system for hybrid approach to natural language understanding, comprising: a machine learning service comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to: create a new natural language understanding model based at least in part by a plurality of user-provided examples; and provide a natural language understanding model dataset comprising at least the new natural language understanding model to other components of the system; an integrated development environment comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to: retrieve the natural language understanding model dataset from the machine learning service; and publish a runtime solution by combining at least a natural language understanding rule and a natural language understanding model dataset; and an interaction engine comprising a memory, a processor, and a plurality of programming instructions stored in the memory thereof and operable on the processor thereof, wherein the programmable instructions, when operating on the processor, cause the processor to: retrieve the runtime solution from the integrated development environment; receive a natural language input from an external interface; process the natural language input by at least annotating and classifying the input; generate a log dataset based at least on how the runtime solution and processed input interprets the natural language input; and store the natural language input, and log dataset to a log storage; wherein the processing of the natural language input uses a hybrid solution comprising both natural language rules and machine learning-based classifiers.

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1. A method comprising: processing by an apparatus one or more data requests to generate at least one query; determining, by the apparatus, one or more algorithms for bounding, at least in part, result data responsive to the one or more data requests, the at least one query, or a combination thereof, based, at least in part, on one or more applications, one or more services, or a combination thereof that are associated with the one or more data requests, the at least one query, or a combination thereof; causing, at least in part by the apparatus, an association of the one or more algorithms with the at least one query; determining, by the apparatus, respective operational granularities of the one or more algorithms; and causing, at least in part by the apparatus, a serialization of the one or more algorithms in a semantic web description format based, at least in part, on the respective operational granularities.

3. A method of claim 1 , further comprising: determining one or more models associated with the one or more algorithms for the bounding of the result data, wherein the one or more models represent, at least in part, one or more data transformations, one or more data extractions, one or more data loadings, or a combination thereof.

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2. The method of claim 1 , wherein: the at least one characteristic of the speech of the telephone caller comprises a plurality of words; the at least one associated characteristic of each word cluster comprises a plurality of associated words; and the determining comprises determining a similarity of the plurality of words and the plurality of associated words of the most similar cluster.

4. The method of claim 2 , wherein: the at least one characteristic of the speech of the telephone caller further comprises at least one acoustic characteristic; the at least one associated characteristic of each word cluster further comprises at least one acoustic characteristic; and the analyzing of the audio data to identify at least one acoustic characteristic of the speech of the telephone caller comprises: correlating each of a plurality of portions of an acoustic or frequency component of the audio data with each of at least a subset of the plurality of words; and determining the at least one acoustic characteristic for how the telephone caller says at least one of the subset of the plurality of words based on the portion of the acoustic or frequency component of the audio data correlated with the at least one of the subset of the plurality of words.

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64. The method of claim 57 wherein the collection resource at a Web site used to collect first activity information comprises a sharing widget.

57. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not identified in the social graph, performing a deterministic fingerprinting approach using attributes comprising at least one of device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, and behavioral patterns; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; determining a first value associated with the first edge based on at least one of the first or second activity information; and adjusting the first value to create a second value associated with the first edge based on a passage of time from at least one of the first or second activity information.

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16. The product of claim 15 wherein after responses from each of the set of approvers are received, an outcome of the requested decision is received.

15. A computer program product encoded on a non-transitory storage medium, the product comprising non-transitory, computer readable instructions for causing one or more processors to perform operations comprising: receiving a request for a decision at a decision manager system, the received request associated with a unique identifier; classifying the request based on metadata associated with the received request; identifying a decision approval rule set based on the classified request, the decision approval rule set identifying a set of approvers and a defined schedule associated with routing requests to the set of approvers; identifying at least one prior approval associated with the unique identifier associated with the received request, the at least one identified prior approval associated with at least one approver among the identified set of approvers, wherein the at least one identified prior approval corresponds to at least one approval associated with a prior, related request to the received request; and reducing time and resources consumed in reaching the decision by applying the at least one prior approval to the decision associated with the received request and automatically updating, at the decision manager system, the set of approvers by automatically applying the at least one prior approval associated with the request in association with the corresponding at least one approver and removing the at least one approver from the set of approvers in the defined schedule associated with routing requests to the set of approvers before sending the request to any approver in the set of approvers; and wherein the identified decision approval rule set defines at least one rule determining when a prior approval of at least one approver is no longer valid based on subsequent actions by at least one other approver in the set of approvers, the operations further comprising, in response to determining that the prior approval of the at least one approver is determined to be no longer valid: removing the at least one prior approval from being applied to the decision associated with the received request and automatically updating the set of approvers to include the at least one approver associated with the no longer valid prior approval and updating the defined schedule routing of requests to include the at least one approver associated with the no longer valid prior approval.

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13. A system for responding to an inquiry comprising: a web miner configured to retrieve a first web page and a second web page, the first web page associated with a first layout and the second web page associated with a second layout and to compare the first layout and the second layout and to generate stored question-answer pairs based on the comparing the first layout and the second layout; an interface configured to receive the inquiry via a network; provide a plurality of responses receive a selection of a particular response from among the plurality of responses; a database comprising stored question-answer pairs; a feature extractor module for extracting features of the stored question-answer pairs from the database and labeling each question-answer pair with meta-level features to define relationships among stored question-answer pairs, the meta-level features of a particular stored question-answer pair based on the meta-level features of a previous related stored question-answer pair and a first related stored question-answer pair; and a processor configured to: clarify the inquiry based on follow-up procedures including asking follow-up questions and analyzing the inquiry to determine the plurality of responses to the inquiry based on the stored question answer pairs, the relationships among the stored question answer pairs, and the follow-up procedures; and store a measure of the eligibility of the particular response to be a response to the inquiry based on the selection.

19. The system of claim 13 wherein the web miner analyzes structure and content of a web page to determine whether the web page has a question-answer pair on it.

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8. A non-transitory computer-readable storage medium storing instructions that, when executed by a computer, cause the computer to perform a method for placing a circuit design, the method comprising: receiving a netlist for the circuit design, wherein the netlist describes interconnections between a plurality of cells; representing the netlist as a graph; performing fuzzy clustering on the graph to obtain a set of clusters and a set of probability values, wherein each probability value corresponds to a probability of a given cell belonging to a given cluster; partitioning the netlist based on the set of clusters and the set of probability values to obtain a partitioned netlist; placing the partitioned netlist to obtain a placed circuit design, wherein cells of each partition are placed in a layout bin corresponding to the partition; and optimizing the placed circuit design, wherein said optimizing reassigns at least one cell to a different layout bin based on the set of probability values.

9. The non-transitory computer-readable storage medium of claim 8 , wherein said representing the netlist as the graph comprises representing each cell as a vertex in the graph, and representing interconnections between a pair of cells as an edge between a pair of vertices corresponding to the pair of cells.

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9. The computer readable storage medium of claim 6 , wherein the configuration tools allow a user to specify one or more filters specifying how annotation fields contained in an annotation structure can be manipulated based on user roles.

6. A computer-readable storage medium containing an executable component for configuring an annotation system for managing annotations created for data objects manipulated by one or more applications on a network which, when executed by a processor, performs operations comprising: identifying a plurality of annotatable heterogeneous data objects, each manipulated by a corresponding one of a plurality of applications on the network, wherein each of the plurality of applications specifies an indexing mechanism for indexing data objects associated with a representative application, and wherein the indexing mechanism for each of the plurality of applications is different from one another; and providing a set of one or more configuration tools configured to: allow a user to define an annotation structure containing one or more annotation fields for annotations created for a respective application, and wherein one or more of the annotation fields are used to store metadata included in a given annotation and wherein one or more of the annotation fields store metadata used to index an annotation according to the indexing mechanism and mapping function associated with the respective application; associate the annotation structure with at least one of the plurality of applications; allow a user to define roles configured to determine the type of information captured or viewed in an annotation created for a given data object of a given application; and associate annotation structures defined by the user with combinations of the user defined roles and annotatable data objects, whereby a subsequent request to annotate a given annotatable data object results in a selection of one or more of the associated annotation structures based on a match between a role of a user making the subsequent request and the role associated with the one or more of the associated annotation structures.

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1. A method of providing cross-domain semantic ranking of complete input phrases for a digital assistant, comprising: receiving a training corpus comprising a collection of complete input phrases that span a plurality of semantically distinct domains; for each of a plurality of distinct words present in the collection of complete input phrases, calculating a respective word indexing power across the plurality of domains based on a respective normalized entropy for said word, wherein the respective normalized entropy is based on a total number of domains in which said word appears and how representative said word is for each of the plurality of domains; for each complete input phrase in the collection of complete input phrases, calculating a respective phrase indexing power across the plurality of domains based on an aggregation of the respective word indexing powers of all constituent words of said complete input phrase; obtaining respective domain-specific usage frequencies of the complete input phrases in the training corpus; and generating a cross-domain ranking of the collection of complete input phrases based at least on the respective phrase indexing powers of the complete input phrases and the respective domain-specific usage frequencies of the complete input phrases.

3. The method of claim 1 , wherein calculating the respective word indexing power across the plurality of domains for each word w i of the plurality of distinct words further comprises: calculating the respective normalized entropy ε i ; for the word w i based on a respective formula ɛ i = - 1 log ⁢ ⁢ K ⁢ ∑ k = 1 K ⁢ ⁢ c i , k t i ⁢ log ⁢ c i , k t i , wherein K is a total number of domains in the plurality of domains, c i,k is a total number of times w i occurs in a domain d k of the plurality of domains, and t i =Σ k c i,k is a total number of times w i occurs in the collection of complete input phrases, and wherein the respective word indexing power of the word w i is (1−ε i ).

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18. The computer program product of claim 10 where the computer-readable program code is configured to provide output of the selected automatons in the form of identifiers of textual content fields found within the input document and locations of the textual content fields found within the input document.

10. A computer program product for scalable, rule-based processing, the computer program product comprising: a non-transitory computer-readable storage medium; and computer-readable program code embodied in the computer-readable storage medium, where the computer-readable program code is configured to construct a plurality of automatons corresponding to a plurality of trigger rules and a plurality of word lists that are employed by the trigger rules, evaluate any of the plurality of trigger rules with respect to an input document by: selecting any of the automatons to evaluate a given one of the plurality of trigger rules, parsing the input document using the selected automatons, determining whether conditions of the given trigger rule are met, identifying any actions that are associated with the given trigger rule, and display in a rule tracing any of the plurality of trigger rules that are evaluated, together with indicia for different portions of the displayed trigger rules indicating an evaluation result of each of the different portions.

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34. A computer implemented method, comprising: using at least one computer system configured for: receiving a SQL statement for a database for compilation, at an auto tuning optimizer and performance information related to the SQL statement; and determining whether one or more statistics relating to the SQL statement are available or accurate in the performance information; determining a hint for a missing or an inaccurate statistic in the performance information; creating or improving an estimate of a value determined by the auto-tuning optimizer for generating an execution plan by sampling an adjustable portion of data of the database without requiring performance of a full table scan and by using a hint based at least in part upon a recursive determination of a relationship between a predicate selectivity and a threshold or a determination of whether an index for the SQL statement exists; and verifying the estimate by executing the SQL statement to perform at least the full table scan based at least in part upon the predicate selectivity, wherein the act of verifying the estimate performs a sample of a result of the full table scan to adjust the estimate.

39. The method of claim 34 , further comprising: using self-corrected information to build auto tuning hints to correct base statistics.

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56. The computer system of claim 55, further comprising means for gathering results from the at least one spawned denizen.

55. The computer system of claim 26, further comprising means for spawning at least one denizen in response to a query.

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16. The method of claim 1 , wherein the validation outcome indicates credentials of the entity to be validated.

1. A computer-implemented method for validating an entity, the method comprising: classifying an entity type of an entity to be validated based on a predefined entity classifier; selecting at least one of a plurality of validation rules in accordance with the entity type; producing, by a computer of a requesting entity and based on the selected at least one validation rule, a validation request including information identifying the entity; providing, by the computer, the validation request to a validation entity for performance of at least a portion of a validation in accordance with the selected at least one validation rule; receiving, by the computer, a validation outcome of the at least the portion of the validation from the validation entity; generating a validation request management display including an inbox icon, an outbox icon, an overview section, and a details section; wherein: responsive to selection of the inbox icon, the overview section displays a list of validation outcomes that have been received and the details section displays detailed information regarding a selected one of the listed validation outcomes; and responsive to selection of the outbox icon, the overview section displays a list of validation requests that have been provided to validation entities and the details section displays detailed information regarding a selected one of the listed validation requests.

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8. A computer storage medium encoding a computer program of instructions for executing a computer process for localization, said computer process comprising: loading one of an application, data or an operating system wherein one of the application, the data or the operating system places a call to a resource loader to load a resource; loading the resource in response to the call to load the resource, wherein the application, data or operating system indicates a language for the resource; intercepting the resource in the resource loader after the resource which is in the language has been received in the loader; converting the resource to a language specific localized resource in a different language if the resource is permitted to be translated based on a comparison with one or more predetermined resource identifier, wherein the converting comprises: comparing the resource to a predetermined set of resource identifiers in a data structure that cannot be modified by a user; when the resource matches one of the identifiers, loading a translation of the resource from a localized language pack; and comparing the translation of the resource to one or more predetermined rules; transmitting the localized resource in the different language to the one of the application, data or operating system; and transmitting the resource in the language without translation if the resource is not permitted to be translated based on a comparison with the one or more predetermined resource identifiers.

9. The computer storage medium of claim 8 wherein if the resource does not comply with the one or more predetermined rules, transmitting the resource in the language without translation to the one of the application, data or operating system.

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4. Method as claimed in claim 1 , wherein at least one unit of at least one target unit sequence has a target duration that is longer or shorter by a predetermined minimal amount than the duration of the corresponding unit of a previously selected waveform unit sequence.

1. A method for converting an input linguistic description into a speech waveform comprising: deriving at least one target unit sequence corresponding to the input linguistic description; assigning in a waveform unit database one or more waveform units to each target unit of the at least one target unit sequence; selecting for the at least one target unit sequence a plurality of alternative waveform unit sequences approximating the at least one target unit sequence, using the one or more waveform units assigned to each target unit of the at least one target unit sequence; concatenating the alternative waveform unit sequences to form alternative speech waveforms; and presenting the alternative speech waveforms to an operating person and enabling the choice of one of the presented alternative speech waveforms.

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24. The method of claim 2 , further comprising: each item having at least one publisher identifier: in the aggregating step, aggregating the annotations for each publisher identifier such that the keywords and the user identifiers associated with the publisher identifier are aggregated from all the annotations corresponding to the publisher identifier; searching based on at least one keyword; determining publisher identifiers that match the at least one searched keyword from the aggregated annotations corresponding to the publisher identifier; and ranking the determined publisher identifiers.

34. The method of claim 24 further comprising each item having at least one publisher identifier, and ranking the publisher identifiers in a category context.

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10. The computer program product of claim 9 , further comprising: computer readable program code configured to prepare an instance of the first web feed document every X minutes; and computer readable program code configured to prepare an instance of the second web feed document every Y>X minutes.

9. A computer program product, comprising: a non-transitory computer readable storage apparatus having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to receive entries from an information technology service running on a server, the entries indicate an amount of CPU capacity which is in use at the server over a first time period, a first severity level associated with the amount of CPU capacity which is in use at the server over the first time period, an amount of CPU capacity which is in use at the server over a second time period which is longer than the first time period, and a second severity level associated with the amount of CPU capacity which is in use at the server over the second time period; computer readable program code configured to prepare a first web feed document from the entries and transmit the first web feed document to a client computing device associated with a first user type, the first web feed document identifying, in a <title> element, the amount of CPU capacity which is in use at the server over the first time period and the first severity level but not the amount of CPU capacity which is in use at the server over the second time and the second severity level; and computer readable program code configured to prepare a second web feed document from the entries and transmit the second web feed document to a client computing device associated with a second user type, the second web feed document identifying, in a <title> element, the amount of CPU capacity which is in use at the server over the second time period and the second severity level but not the amount of CPU capacity which is in use at the server over the first time and the first severity level.

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17. A method performed at least in part on at least one processor, said method comprising: receiving an image to classify, said image being located within a first web page; identifying a plurality of web pages comprising said image by transmitting a search request to a search system and returning said plurality of web pages, the first web page included in said plurality of web pages; identifying a training set of examples from at least one of said web pages, said training set of examples comprising a subset of said text within said plurality of web pages, the subset of said text being classified based on a determination of a measure of proximity to said image, said training set comprising at least one positive example and at least one negative example; training a classifier using said training set, said classifier being a binary classifier; and classifying said text within said plurality of web pages using said classifier to identify a group of text associated with said image.

20. The method of claim 17 , wherein said web page comprises a HyperText Markup Language (HTML) document.

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28. The computer-program product of claim 23 , wherein the target time difference is a setpoint for a homeostatic process involving the artificial neuron.

23. A computer-program product for learning using a spiking neural network, comprising a non-transitory computer-readable medium comprising instructions executable to: (a) delay an input spike in an artificial neuron according to a current delay associated with an input to the artificial neuron, wherein the input spike occurs at an input spike time relative to a reference time for the artificial neuron; (b) emit an output spike from the artificial neuron based, at least in part, on the delayed input spike; (c) determine an actual time difference between the emission of the output spike from the artificial neuron and the reference time for the artificial neuron; and (d) adjust the current delay associated with the input based on a difference between a target time difference and the actual time difference, the current delay, and an input spike time for the input spike.

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1. A computer-implemented method comprising: (A) receiving a search query; (B) providing a first user interface, the first user interface displaying first search results specifying resources that a search engine has identified as being responsive to the search query, the first user interface further displaying a subject matter link identifying a particular subject matter that the search engine has identified based on the first search results, the particular subject matter being associated with a particular collection of records that the search engine has selected from among multiple collections of records, all records in the particular collection having a common attribute structure of data elements that pertain to the particular subject matter, (C) wherein the first user interface further displays a second subject matter link identifying a second subject matter that the search engine has also identified based on the first search results, the second subject matter being associated with a second collection of records that the search engine has selected from among the multiple collections of records, all records in the second collection having a common attribute structure of data elements that pertain to the second subject matter, the common attribute structure of the second collection being different than the common attribute structure of the particular collection; (D) receiving a selection of the subject matter link; (E) formatting second search results based on a template that is associated with the particular subject matter, each of the second search results specifying a respective record, each record being in the particular collection of records associated with the particular subject matter; and (F) providing a second user interface that displays the second search results and an interface element that is associated with the template.

2. The method of claim 1 , wherein the second user interface displays the second search results in a table, wherein each row of the table refers to a single resource and each column of the table refers to a single attribute from the common attribute structure of the data elements.

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6. The method of claim 1 , wherein the one or more of the plurality of advertising files belongs to a corresponding one of a plurality of product categories.

7. The method of claim 6 , wherein each of the plurality of categories is associated with a distinct set of phonemes, and wherein the corresponding one of the plurality of product categories is associated with the second set of phonemes.

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1. A computer system for editing text data, which have been created on a basis of a voice or a video image, comprising: a first computer for outputting one or more of said voice or said video image, and for identifying text data which needs to be edited, in response to a received instruction, the text data comprising a plurality of parts of text data; a plurality of computers for outputting said voice or said video image, and for editing said plurality of parts of text data, which have been identified by said first computer, in response to said received instruction; and an allocation determination unit, said allocation determination unit retrieving each of the one or more of said voice or said video images and allocating each of said one or more of said voice or said video images to one of the plurality of computers by optimally selecting one of the plurality of computers, wherein said optimally selecting comprises: determining a number of vacant client computers; determining a number of said one or more said voice or said video images have not been processed; processing one of the one or more of said voice or said video images by a vacant client computer responsive to determining that the number of one said one or more said voice or said video images that have not been processed is greater than one, and the number vacant client computers is one, wherein processing requirements of said one of the one or more of said voice or said video images matches processing requirements of the vacant client computer; processing one of the one or more of said voice or said video images by a vacant client computer responsive to determining that the number of one said one or more said voice or said video images that have not been processed is one, and the number vacant client computers is greater than one, the processing comprising calculating a job optimum degree, the job optimum degree based on a weighted latency of each of the vacant client computers, wherein the weighted latency does not correspond linearly with the latency, and the processing is performed on the vacant client computer with a maximum job optimum degree; and delaying the processing one of the one or more of said voice or said video images by a vacant client computer responsive to determining that the number of one said one or more said voice or said video images that have not been processed is one, and the number vacant client computers is one, the delaying comprising calculating a job optimum degree, the job optimum degree based on a weighted latency of the vacant client computer, wherein the weighted latency does not correspond linearly with the latency, and preventing processing of the one of said one or more of said voice or said video images by the vacant client computer in response to determining that the job optimum degree exceeds a threshold; wherein said first computer distributes said voice or said video image, one of said plurality of said parts of text data which needs to be edited, and one or more editing instructions, to each of said plurality of computers for parallel processing, each of said plurality of computers automatically outputting said voice or said video image, which corresponds to said one of said plurality of parts of text data, prior to editing said plurality of parts of text data.

5. The computer system according to claim 1 , wherein each of said plurality of computers outputs an additional voice or an additional video image, each corresponding to other parts of text data related to said one of said plurality of parts of text data which needs to be edited, in a form which is different from that for said voice or said video image, each corresponding to said one of said plurality of parts of text data.

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12. The non-transitory computer readable storage medium as recited in claim 9 , further comprising instructions that, when executed by the at least one processor, cause the computer system to: determine a probability that a second unknown person instance in the image is each of the plurality of known person instances from images in the image gallery; and jointly determine the context weight for each combination of the first unknown person instance and each known person instance from the plurality of known person instances and each combination of the second unknown person instance and each known person instance from the plurality of known person instances.

9. A non-transitory computer readable storage medium comprising instructions that, when executed by at least one processor, cause a computer system to: determine a probability that a first unknown person instance in an image is each of a plurality of known person instances from images in an image gallery; identify a plurality of context cues between one or more of the first unknown person instance and one or more known person instances of the plurality of known person instances or between known person instances of the plurality of known person instances; determine a context weight for each combination of the first unknown person instance and each known person instance from the plurality of known person instances using a conditional random field algorithm based on the identified plurality of context cues; calculate a contextual probability based on the determined probabilities and the determined context weights; and identify the first unknown person instance as a known person instance from the plurality of known person instances with a highest contextual probability.

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5. The method of claim 4 , further comprising: comparing the score for each one of the recognition hypotheses to a score threshold; wherein the score of the recognition hypothesis is selected as the recognition result for the natural language input exceeding the score threshold.

4. The method of claim 3 , further comprising: generating a score for each one of the recognition hypotheses; wherein the recognition hypothesis selected as the recognition result for the natural language input is selected based on the score.

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6. The method of claim 5 , wherein: said region is smaller than said field of view, and is substantially fully within said field of view.

5. The method of claim 1 , further comprising: establishing an imaging field of view; and defining a said region in said field of view; wherein: detecting said actor input comprises receiving at least one image of said field of view, with said actor input therein and in said region.

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26. The computing device of claim 25 wherein, if said portion does not have more than said threshold number of characters, said determining said pronunciation of said username further comprises generating a phonetic representation of each character of said portion pronounced individually or generating a tokenized representation of each individual character of said portion suitable for interpretation by a text-to-speech engine.

25. The computing device of claim 19 wherein said calculating said likelihood of pronounceability is conditional upon said portion having more than a threshold number of characters.

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8. The handheld media storage and retrieval device according to claim 1 , wherein when the selection of the one element of the first list of elements is received by the selection component, at least some of the first list of elements are displayed according to the first orientation as the new headers of the new screen, wherein text corresponding to the at least some of the first list of elements include nouns and verbs and wherein only nouns included in the text corresponding to the at least some of the first list of elements are displayed as the new headers.

1. A handheld media storage and retrieval device, comprising: a display device displaying a display screen for viewing media content stored on the handheld media storage and retrieval device, the display screen displaying only a hierarchical menu comprising only two hierarchical levels of a plurality of hierarchical levels of the stored media content; a user input mechanism on the handheld media storage and retrieval device, the user input mechanism accepting user commands and information; a first input component for navigating initial headers representing a first one of the plurality of hierarchical levels and organized in a first orientation displayed on the display screen of the handheld media storage and retrieval device, wherein each of said initial headers includes an association with a child list, whereby said initial headers form a band of lists represented by the initial headers; a second input component for navigating a first list of elements representing a second one of the plurality of hierarchical levels and organized in a second orientation different from the first orientation, the first list of elements associated with a currently selected header of the initial headers displayed as a child list for the currently selected header; and a selection component for receiving a selection of one element of the first list of elements, wherein, upon the selection of the one element of the first list of elements, the first list of elements become new headers and at least some of the first list of elements are displayed according to the first orientation as new headers of a new screen, the new headers including the one selected element as a new currently selected header of the new screen and displayed in an order determined by the selection, and a second list of elements representing a third one of the plurality of hierarchical levels is displayed in the second orientation, the second list associated with the new currently selected header as a child list for the new currently selected header, the new screen displaying only the new headers and the second list, and wherein navigating and selecting is repeated until a particular hierarchical level comprising atomic elements is displayed in the second orientation, wherein upon selection of an atomic element of the atomic elements, the display screen displays only the particular hierarchical level in the first orientation with the selected atomic element as an active header and an information display box containing information about the selected atomic element.

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14. A method, implemented in a computing system, comprising: receiving a base language content piece from a content provider; receiving a request for a mixed language version the content piece from a user; receiving an assessment associated with the user's proficiency with a plurality of foreign language words; and producing the mixed language version of the content piece by a processor, the mixed language version including a first foreign language word from the plurality of the foreign language words substituted for all of the instances of a corresponding first base language word occurring in the base language content piece when the assessment indicates that the user is proficient with the first foreign language word, the mixed language version including a second foreign language word from the plurality of the foreign language words substituted for a portion of the instances of a corresponding second base language word occurring in the base language content piece when the assessment indicates that the user is less than proficient with the second foreign language word.

18. The method of claim 14 wherein the base language content piece is a novel.

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1. A method for computerized batching of huge populations of electronic documents, including computerized assignment of electronic documents into at least one sequence of electronic document batches such that each document is assigned to a batch in the sequence of batches and such that absent conflict between batching requirements, the following batching requirements being maintained by a suitably programmed processor: a. pre-defined subsets of documents are always kept together in the same batch b. batches are equal in size c. the population is partitioned into clusters and all documents in any given batch belong to a single cluster rather than to two or more clusters, the method also comprising filling batches, separately for each of several clusters, including first using large keep-together sets as batches and then combining keep-together sets other than the large sets into batches and finally ordering the resulting batches into a sequence according to urgency.

8. The method according to claim 1 wherein requirement (a) (keep-together) takes precedence over requirement (c)—that each batch include only documents belonging to a single cluster—in that an artificial intelligence functionality uniformizes the cluster id's of all documents having a single keep-together id.