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63. The speech synthesizer of claim 62 wherein said plurality of resonant filters are connected in cascaded form.

62. The speech synthesizer of claim 61 wherein said vocal tract includes a plurality of resonant filters including at least one resonant filter that is adapted to resonate at a frequency higher than the high frequency formant added to said voiced excitation signal.

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50. The method of claim 47 further comprising: selecting a second digital file having a second digital data content, using said information management software application, before said step of opening said first base format document using said third-party document generation application on said computer-based platform; and dragging and dropping said selected second digital file into a displayed second data holder location defined by said first document layout of said first base format document, using said information management software application, such that said second data holder location of said first base format document is populated with said second digital data content before said step of opening said first base format document using said third-party document generation application on said computer-based platform.

57. The method of claim 50 wherein said second digital file comprises a graphic file and said second digital data content comprises a graphic.

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8. The processing apparatus of claim 7 , wherein the at least one processor is further configured to: reconfigure at least one row of the big data database using the row ID of the data included in the dictionary.

7. The processing apparatus of claim 6 , wherein the dictionary includes a row ID for identifying a row order in the big data database of each data included in a data block is stored in association with corresponding data.

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20. The contact center of claim 19 , wherein the work assignment engine includes the IVR script.

19. A contact center, comprising: a work assignment mechanism contained in memory and executed by a processor, the work assignment mechanism including: a work assignment engine configured to compare attributes of work items in a work pool with attributes of resources in a resource pool and match the work items to resources based on the comparison of attributes; and an IVR script configured to analyze a work item for work assignment information, wherein the work item represents a contact received at a contact center, determine whether the work assignment information includes customer information for assigning the work item to a resource of the contact center other than an interactive voice response (IVR) resource, determine a first IVR resource of a plurality of IVR resources that is capable of obtaining a first portion of the customer information when the work assignment information does not include the customer information, and assign the work item to the first IVR resource when it is determined that the work assignment information does not include the customer information, wherein the first IVR resource is configured to execute a first IVR function configured to obtain the first portion of the customer information, wherein the first IVR function represents an individual IVR function that is separate and apart from an IVR unit and other IVR functions, and wherein the first IVR resource is configured to automatically return the work item to the work assignment engine after executing the first IVR function.

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18. The system of claim 17 , wherein the one or more computers are further configured to perform operations including: receiving a relevance score for each of the plurality of distinct book content items, the relevance score being a measure of relevance of the distinct book content item to a search query; ranking the plurality of distinct book content items based on the rank score and the relevance score; and ordering search results for the book content items, the search results being ordered according to the ranking of the plurality of distinct book content items.

17. A system, comprising: a memory, the memory storing a plurality of distinct book content items and corresponding characteristics of the distinct book content items; and one or more computers configured to interact with the memory, the one or more computers being further configured to perform operations including: segmenting textual content for each of the plurality of distinct book content items into word strings, each word string including a predefined number of contiguous words in the textual content of a book content item; classifying word strings having a frequency of occurrence that is less than a threshold frequency of occurrence as uncommon word strings, the frequency of occurrence for each word string being a number of occurrences of the word string relative to the total number of word strings in the plurality of distinct book content items; representing a weighted graph in the memory, the weighted graph including a plurality of distinct nodes, each distinct node representing a corresponding distinct book content item in the plurality of distinct book content items, and where an edge exists in the weighted graph between each pair of distinct nodes that represent distinct book content items that both include a matching uncommon word string, each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching word strings in the textual content of other distinct book content items that are represented by other distinct nodes, each matching word string being a word string that matches an uncommon word string in the textual content of the distinct book content item corresponding to the distinct node; and generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of an uncommon word string to one or more matching word strings in the textual content of another distinct book content item; and determining a rank score for each distinct book content item based on the edges between the distinct nodes representing the distinct book content items, the rank score being a score indicative of the importance of each distinct book content item relative to other distinct book content items.

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18. The method of claim 1 , wherein the aligning step further comprises: dividing the at least one portion of the caption data stream into a plurality of discrete caption data segments; selecting a first group of two or more audio stream segments; comparing the first group of audio stream segments to a first caption data segment to determine if a correlation exists between the first caption data segment and at least one of the two or more audio stream segments in the first group of two or more audio stream segments; if the correlation does not exist, assessing whether at least one of the two or more audio stream segments in the first group of two or more audio stream segments has an association with a successive caption data segment; and if the association does not exist, repeating the assessing step until an association is found between at least one of the two or more audio stream segments and at least one of the plurality of discrete caption data segments.

1. A method in a computer system for caption synchronization of media programs comprising receiving at least one portion of a media stream and at least one portion of a caption data stream in the computer system, wherein the at least one portion of the media stream and the at least one portion of the caption data stream correspond to an event; and the at least one portion of the media stream comprises timing information and at least one audio component; and utilizing at least one processing unit in the computer system to translate an audio signal into a sequence of word sounds in an audio stream; divide the audio stream into a plurality of overlapping audio stream segments that each correspond to a respective time slice of the audio stream, wherein each audio stream segment overlaps with a temporally adjacent audio stream segment such that temporally adjacent audio stream segments share a portion of the audio stream; translate the audio stream into a string of words using a combination of a base language model and an event specific language model; produce an audio-processed transcript by executing an indexing engine on the string of words, wherein the audio processed transcript includes a text stream of at least a plurality of sequences of words and timing information; align the audio-processed transcript with the at least one portion of the caption data stream; and generate a time synchronized caption data stream by applying the timing information from the audio-processed transcript to the at least one portion of the caption data stream based on the aligning.

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16. The method of claim 15 , further comprising: determining if the function name associated with the tooltip information has been selected; and if the function name has been selected, then displaying a help topic corresponding to the function name.

15. A method for providing an interactive tooltip, the method comprising: receiving an indication that a function is being entered in an editing location of an electronic document, wherein the electronic document comprises a spreadsheet and the editing location comprises a data cell of the spreadsheet; receiving a function name from the editing location of the electronic document; recognizing the function name in response to a user entering the function name; retrieving tooltip information associated with the recognized function name, wherein the tooltip information includes the function name and an argument associated with the function name comprising a description of data required by a formula associated with the function name, the tooltip information identifying the argument name as being currently entered; displaying the tooltip information in a display location, the display location being proximate to the editing location of the electronic document; determining if the argument name associated with the tooltip information has been selected; and if the argument name has been selected, then displaying a help topic corresponding to the argument name.

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1. A computer-implemented method for optimizing a task graph that delineates a plurality of tasks to be evaluated in a parallel processing environment, the method comprising: generating a first task aggregation topology associated with the task graph that divides the plurality of tasks into a first collection of sets, wherein each set in the first collection of sets includes one or more tasks from the plurality of tasks, each task of the plurality of tasks belongs to only one set included in the first collection of sets, and the first task aggregation topology comprises a bit mask that indicates two or more tasks of the plurality of tasks that are included in a first set in the first collection of sets; compiling the plurality of tasks according to the first task aggregation topology to generate units of work to be executed in the parallel processing environment, wherein the two or more tasks included in the first set are compiled to generate a single unit of work that is executed by a first processing engine included in the parallel processing environment; collecting statistics associated with executing the units of work in the parallel processing environment; and determining whether the first task aggregation topology is more efficient in execution than any previously-defined task aggregation topology based on the statistics; and if the task aggregation topology is more efficient in execution than any previously-defined task aggregation topology, then selecting the first task aggregation topology as the most optimal task aggregation topology, or if the first task aggregation topology is not more efficient in execution than any previously-defined task aggregation topology, then selecting a second task aggregation topology as the most optimal task aggregation topology.

5. The method of claim 1 , wherein determining whether the first task aggregation topology is more optimal than a previously-defined task aggregation topology comprises comparing the statistics associated with executing the units of work in the parallel processing environment with previously-collected statistics associated with executing units of work in the parallel processing environment based on a previously-defined task aggregation topology.

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1. A computer-implemented method, comprising: receiving multiple data snippets, each of the data snippets comprising one or more n-grams; processing each of the data snippets by: identifying n-grams in the corresponding data snippet that have not occurred in any of the data snippets processed prior to the corresponding data snippet, as unseen n-grams, and computing a snippet score for the corresponding data snippet based on a frequency of the unseen n-grams and a length of the corresponding data snippet; sorting the data snippets based on the snippet scores to generate sorted data snippets; selecting, based on a first specified criterion, one or more of the sorted data snippets as training data for a language processing engine; and storing the training data in a memory, wherein the training data is to be used by the language processing engine to perform automated language processing functions.

9. The computer-implemented method of claim 1 , wherein selecting the one or more of the sorted snippets includes adding a first data snippet of the sorted data snippets having a highest snippet score in the sorted data snippets to the training data.

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3. A method of claim 1 , wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following: a processing of the at least one request to determine a requested segment of the selected at least one user model; and a generation, a retrieval, or a combination thereof of the requested segment based, at least in part, on whether the requested segment exists.

1. A method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on the following: an ontology for specifying a hierarchy of one or more abstraction levels for items data used in latent factorization models; a generation, by at least one processor implemented in hardware, of one or more user models for the items data corresponding to each abstraction level of the ontology; a processing of at least one request for one or more recommendations (a) to determine a requested abstraction level, and (b) to determine a privacy level, a security level, or a combination thereof associated with the at least one request; a processing of the privacy level, the security level, or the combination thereof against one or more privacy policies, one or more security policies, or a combination thereof to determine permission to access the requested abstraction level; a generation, a retrieval, or a combination thereof of the at least one of the one or more user models based, at least in part, on whether the at least one of the one or more user models exists at the requested abstraction level, a selection of at least one of the one or more user models for generating the one or more recommendations for one or more applications, one or more services, or a combination thereof based, at least in part, on the one or more privacy policies, the one or more security policies, or the combination thereof; and wherein the one or more abstraction levels correspond to different levels of the privacy policies and the security policies of the one or more user models.

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12. The electronic device of claim 11 , wherein the input field targeting characteristic is selected from the group consisting of: a location of a majority of the handwriting input strokes, a location of an initial handwriting stroke, a location of a baseline of the handwriting input strokes, and a center of gravity of the handwriting input strokes.

11. An electronic device, comprising: an input and display device; a processor; and a memory device that stores instructions executable by the processor to: present, on the input and display device, two or more adjacent input fields for an underlying application; detect, using the input and display device, one or more handwriting input strokes provided to an input field overlay application, wherein the input field overlay application encompasses the two or more adjacent input fields and wherein at least a portion of the one or more handwriting input strokes are detected outside a boundary of the two or more adjacent input fields; determine an input field targeting characteristic based on the one or more handwriting input strokes, wherein the input field targeting characteristic identifies one of the two or more adjacent input fields for insertion of the one or more handwriting input strokes; select the identified one of the two or more adjacent input fields as a target input field based on the input field targeting characteristic; and insert a converted form of the one or more handwriting input strokes into the target input field.

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12. The apparatus of claim 10 , wherein the speech recognition candidate is selected based on a comparison of the computed properties of the given region with the two or more speech recognition candidates generated based on the speech input.

13. The apparatus of claim 12 , further comprising interpreting the selected speech recognition candidate as a portion of an action command.

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17. The computer readable medium of claim 13 , wherein determining a best match pair comprises, for each token of the first attribute, finding a first match pair in the match list, wherein the first match pair comprises the token and the first match pair has a higher score than any other match pair in the match list.

13. The computer readable medium of claim 12 , the instructions translatable for: if no match exists between the pair of tokens, forming a match pair from the pair of tokens and a mismatch penalty and adding the match pair to the match list.

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1. A method for querying a database comprising: identifying an interface to the database for receiving a query including path expressions by a database management apparatus; receiving input defining a compliance rule, the input including: i) input identifying a configuration-item type, the identified configuration-item type determining a type of configuration item in an IT infrastructure of different types of configuration items; ii) input defining a rule scope, the rule scope determining which configuration items of the identified type are to be checked by the compliance rule; and iii) input defining a desired state for each of the configuration items to be checked by the rule, the desired state including at least one compliance condition that must be satisfied for a checked configuration item to be in compliance; receiving input identifying at least one path, each path being from an object in an object model to a related object in the object model or to an attribute of a related object in the object model; creating a path expression for each identified path, each path expression being composed from tokens selected from the group consisting of object identifiers, attribute identifiers, a relationship operator, and path qualifiers, the tokens sequentially added together to create the path expression; displaying at least one list of selectable items, each item associated with a token; receiving selection of at least one of the selectable items; including the at least one token associated with the selected at least one item into the path expression for one of the identified paths; creating a query for querying data structured in accordance with the object model, the query including at least one of the created path expressions; and executing the query on the database to query the data.

3. The method of claim 1 , wherein the object model is an object model for an IT infrastructure.

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6. The computer-implemented method of claim 5 , wherein said reconciliation tool is further configured for, upon detecting one or more differences, providing said user with tools for performing each of: changing field values in the document open in said document creation application to the field values of the version of a document on said platform; and confirming the field value of one or more difference.

5. The computer-implemented method of claim 1 , wherein said reconciliation tool is further configured for highlighting said flagged objects in a user interface of said document creation application to indicate the presence of an object having a field value.

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7. The method according to claim 6 , wherein the video frame produced by the video display device invoking a command to a television signal access device in order to generate a screen of descriptive metadata.

6. The method according to claim 1 , carried out in a television video display device.

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27. A computer-implemented method comprising: using a first software module to access the web page content to retrieve address information for a second software module, the first software module to access hypertext markup language (HTML) web content including the address information and the HTML web content accessible to a web browser, wherein the second software module comprises a non-browser application; automatically identifying a variable value signifying the address information associated with a hypertext element within a hypertext document for the web page; automatically extracting the address information data; providing the extracted address information data as input data to the second software module; and requesting to display an overlaying icon corresponding to the second software module on a user interface, the second software module to access the address information.

32. The method of claim 27 , further comprising automatically locating the hypertext element in the hypertext document in response to an indication provided in response to a display of the web page.

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20. A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors of a computing system, cause the computing system to: receive a first request to cause a temporary password information to be added to a set of password information comprising a plurality of instances of password information, the first request received in response to a login to a multi-tenant computing environment, the set of password information associated with the user and at least one of the instances of password information in the set of password information corresponding to a password known to the user, the set of temporary password information available for generating a ticket granting ticket (TGT); receive a second request for authentication information to be provided to a target component; determine, based at least in part on the second request for authentication information, that the target component to receive the authentication information is not configured to accept the TGT; and generate a response to the second request for authentication information including at least a subset of the set of password information when the target component is determined as not being configured to accept the TGT.

21. The non-transitory computer-readable storage medium of claim 20 , wherein the temporary password information is generated in response to the first request.

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18. The computer-implemented method of claim 12 , further comprising: restarting the batch job, by the batch container, responsive to a failure to commit.

12. A computer-implemented method of batch processing with a batch container of a batch component model in a distributed object environment, the computer-implemented method comprising: forming a contractual relationship between a batch component and the batch container; wrapping the contractual relationship between the batch component and the batch container to form an adapter, wherein the adapter isolates the batch component from different implementations of the batch container; computing, by the batch container on a processor of a data processing system, for each use of a checkpoint interval, a size of the checkpoint interval for a batch component of a batch job based on a set of deployment descriptors and other processing workloads, wherein the set of deployment descriptors is a set of declarative policies for the batch component; running the batch component within the checkpoint interval, by the processor; and upon completion of the checkpoint interval, committing by the batch container, data updated during the checkpoint interval and at least one checkpoint cursor to a storage of the data processing system, wherein context information, including the size of the checkpoint interval and resource dependencies, is persisted and passed to downstream batch containers.

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1. A method, comprising: receiving, using one or more processing units, a search query, wherein the search query is received by a software component; parsing, using the one or more processing units, the search query into keywords and non-keywords; identifying, using the one or more processing units, a category for each keyword in the search query; grouping, using the one or more processing units, the keywords according to category, wherein categories include a file type, wherein metadata associated with a file type includes one or more parameters, wherein a parameter specifies a rule, and wherein grouping the keywords includes linking keywords in the same category using a Boolean OR; generating, using the one or more processing units, a machine interpreted search query by linking the grouped keywords with the non-keywords using a Boolean AND; and transmitting, using the one or more processing units, the machine interpreted search query, wherein when the machine interpreted search query is received by another software component, the machine interpreted search query is used to perform a search.

6. The method of claim 1 , further comprising: generating, using the one or more processing units, a combined set of groups by linking the groups of keywords together using a Boolean AND, wherein generating a machine interpreted search query includes linking the combined set with the non-keywords using a Boolean AND.

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3. The method of claim 2 further comprising: providing the first indicator to the first ASM and the second indicator to the second ASM; performing the functionality for the first particular application by the first ASM in response to receiving the first indicator; and performing the functionality for the second particular application by the second ASM in response to receiving the second indicator.

2. The method of claim 1 further comprising: determining by the SAS to provide a second indicator to the second ASM based on ascertaining the non-semantic speech characteristic; and determining by the SAS not to provide the second indicator to the first ASM.

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6. The non-transitory computer readable storage medium according to claim 1 , wherein the second electronic device is configured to: after forgoing responding to the audio input received using the second microphone in accordance with receiving the stop instructions from the first electronic device: resume responding to the audio input received using the second microphone.

1. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a first electronic device with a display, a first microphone, cause the first electronic device to: sample an audio input using the first microphone; in accordance with the sampling of the audio input using the first microphone, send stop instructions to a second electronic device with a second microphone, the second electronic device external to the first electronic device, wherein the second electronic device is configured to respond to the audio input received using the second microphone, and wherein the stop instructions instruct the second electronic device to forgo responding to the audio input received using the second microphone, wherein responding to the audio input received using the second microphone comprises providing perceptible output.

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5. The method of claim 1 , wherein the second structured data includes one or more emails.

1. A method for searching sources of data, comprising steps of: capturing unstructured broadcast data from a broadcast source by using a listening device, wherein the broadcast source includes one or more of a television broadcast source and a radio broadcast source; converting the captured unstructured broadcast data to a first structured data, the converting comprising detecting an audio component of the captured unstructured broadcast data and converting the audio component to structured text; receiving a second structured data from a source different from the broadcast source; capturing a digital image from a source different from the second structured data source, wherein the digital image includes graphical text elements recognizable as text by optical character recognition software; converting the graphical text elements of the digital image to a third structured data, the third structured data comprising structured text from the graphical text elements; generating text of contents of each of the first structured data, the second structured data, and the third structured data and storing the generated text on a searchable data storage device; parsing the stored text by (i) collecting only phrases relevant to a specified field and (ii) grouping phrases recognized as comprising temporal references; receiving a search phrase and a selection of a particular language from a user; semantically analyzing the parsed text by ignoring any text not in the particular language; searching the semantically analyzed text using the received search phrase; generating search results based on searching the semantically analyzed text; and providing the search results for communication to the user.

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14. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving text corresponding to at least a portion of a user input; executing a first natural language understanding (“NLU”) process using the text, wherein the first NLU process is associated with a first subject matter, wherein the first NLU process produces a first NLU result, and wherein the first NLU result is associated with a first score indicative of a confidence in the first NLU result; executing a second NLU process using the text, wherein the second NLU process is associated with a second subject matter, wherein the second NLU process generates a second NLU result, and wherein the second NLU result is associated with a second score indicative of a confidence in the second NLU result; selecting the first NLU result based at least partly on the first score and the second score; and generating a response based at least partly on the first NLU result.

17. The computer-implemented method of claim 14 , wherein the first NLU result comprises an interpretation of the text as one of: a request for information regarding the first subject matter; a statement comprising information regarding the first subject matter; or a request for execution of a command associated with the first subject matter.

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16. The system as recited in claim 15 , wherein said determiner-of-auction-format-based-on-evaluating-market-outcome is further configured for: selecting a best auction format, wherein said best auction format comprises the candidate auction format within said plurality of candidate auction formats having the highest of said rankings; and outputting said best auction format.

15. The system as recited in claim 9 , wherein said determiner-of-auction-format-based-on-evaluating-market-outcome is further configured for: receiving a third user input, wherein said third user input comprises a plurality of candidate auction formats; receiving a predicted outcome for each of said candidate auction formats; calculating descriptive statistics for each of said candidate auction formats, wherein said descriptive statistics comprise a mean and a variance; ranking each of said candidate auction formats with respect to said calculated mean and generating corresponding rankings for said plurality of candidate auction formats; and outputting said descriptive statistics and said rankings.

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14. The virtual assistant system of claim 13 , wherein the context information analyzed by the assistant server includes at least one of a location of the mobile device when the command is input, a time of day when the command is input, co-presence of specific individuals, involuntary actions by a user, and action sequences taken by a user of the mobile device.

13. The virtual assistant system of claim 1 , wherein the assistant server analyzes context information of the input command to modify the semantic atom.

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10. A non-transitory computer-readable storage medium having computer-executable instructions stored thereon that, when executed by a computing device, cause the computing device to at least: receive a structured document; parse structural elements from the structured document; generate a text string representing a structure of the structured document from the structural elements, wherein the text string does not comprise textual content from the structured document; derive metadata from the structured document; add the metadata to the text string, the metadata representing a complexity value of the structure of the structured document based at least in part upon a maximum depth of nested structural elements in the structured document; group structural elements in the text string into N-grams utilizing a sliding window; utilize a classifier trained from a plurality of training documents labeled as belonging to a first document class to determine a probability that the structured document belongs to the first document class based on the N-grams, the classifier using the complexity value of the structure of the structured document as a coefficient for a first probability that the structured document belongs to the first document class, wherein the complexity value has a relatively lower value for a first set of documents that are similar and include a simple structure while the complexity value has a relatively higher value for a second set of documents that are relatively less similar and include a relatively more complex structure as compared to the first set of documents; determine whether the first probability that the structured document belongs to the first document class satisfies a threshold value; if the first probability that the structured document belongs to the first document class satisfies the threshold value, classifying the structured document as belonging to the first document class; and if the first probability that the structured document belongs to the first document class does not satisfy the threshold value, utilizing the classifier trained from a plurality of training documents labeled as belonging to the second document class to determine a second probability that the structured document belongs to the second document class based on the text string representing the structure of the structured document.

20. The non-transitory computer-readable storage medium of claim 10 , wherein the complexity value is further based at least in part on at least one of a number of tags in the structured document or a number of different tags in the structured document.

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12. The method as recited in claim 9 , wherein desensitizing the tree comprises: providing a set of ordered desensitization characters; generating a list of counters, wherein each counter corresponds to a quantity of sensitive characters on a node of the tree; and based on the counter for each node, randomly selecting desensitization characters from the set of ordered desensitization characters; and assigning the selected desensitization characters to the corresponding node in an ordered manner.

9. A method of desensitizing sensitive strings, comprising: generating, by a processing device, a set of ordered sensitive strings; generating, by the processing device, a tree corresponding to a first portion of the set of ordered sensitive strings, wherein the tree comprises a first plurality of nodes containing sensitive characters of the first portion of the ordered sensitive strings and leaf nodes corresponding to an end of each sensitive string in the first portion; desensitizing, by the processing device, the tree by assigning desensitization characters to respective ones of the sensitive characters on the nodes of the tree in depth-first order; and generating, by the processing device, a set of desensitized strings, where a desensitized string is added to the set of desensitized strings whenever a leaf node is reached in the tree during the desensitization, and where the desensitized strings include corresponding strings of the desensitization characters.

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4. The method of claim 3 , wherein the sequence level distance is equal to the sum of object level distances for each pair of corresponding objects in the candidate sequence-reference sequence pair, and wherein an object level distance for a given pair of objects is the sum of the attribute level distances for the given pair of objects.

3. The method of claim 2 further comprising associating, by the processor, each candidate sequence with a distance metric indicative of the sequence level distance between the given candidate sequence and the reference sequence, and wherein the candidate sequence best matching the reference sequence is the candidate sequence associated with the lowest distance metric.

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6. The method as claimed in claim 1 wherein the identifier terms associated with the semi-structured or unstructured documents comprise words or phrases found in the body of the semi-structured or unstructured documents.

1. A method of searching a plurality of documents comprising the steps of: providing a search interface having a search term input window for receiving user entered search terms, a search initiation button, one or more search term clarification buttons which, when selected, assign one or more specific additional search terms to one or more user entered input search terms, and a plurality of search result display windows; receiving the one or more user entered input search terms into the search term input window and initiating a search; searching a plurality of structured or unstructured documents for documents related to the one or more user entered input search terms; classifying search results into a plurality of search results classes based on search identifier terms associated with the semi-structured or unstructured documents included in search results; determining a perceived relevance for the plurality of search results classes based at least in part on a popularity of the search identifier terms associated with the search results classes as determined from prior searches including at least one of the one or more user entered input search terms, and wherein the determining further based at least in part by an aggregate document similarity score for the structured or unstructured documents identified by the search of semi-structured or unstructured documents calculated based on a number of times a search identifier term associated with a class is included in the related documents, so that the perceived relevance is determined at least in part by actions of prior users; displaying the search results in the plurality of search result display windows such that different search result display windows display search results related to different search result classes, and wherein the plurality of search results display windows are displayed in a changeable order determined by the perceived relevance of the search results classes, and refining the search results upon receiving a selection of one or more of the search term clarification buttons either before or after receiving a user entered search term in the search window.

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20. The computer-readable medium of claim 19 , wherein identifying the user further comprises applying pattern recognition techniques to the content.

19. The computer-readable medium of claim 18 , the operations further comprising identifying the user of the second device using content of the digital file, the nametag, and the identifiers.

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13. The method of claim 10 , wherein the identifying of the color of the line segment comprises applying a binary classifier to a portion of the image to identify a portion of the image depicting the line segment.

10. A method comprising: accessing an image comprising a depiction of a page region; determining portions of the image depicting text within the page region: identifying a line segment depicted in the image, the line segment having a first part within one or more of the portions of the image depicting text and a second part outside of the portions of the image depicting text; identifying a color of the line segment, based on the second part of the line segment depicted in the image outside of the portions of the image depicting text; determining a difference value between the color of the line segment and a color of each element of the portions of the image depicting; and identifying, by one or more processors of a machine, the text by performing optical character recognition on the portions of the image depicting text while ignoring elements within the portions of the image depicting text that have the color of the line segment.

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13. The method of claim 10 further comprising modifying content of an existing knowledge tip in the tips repository, wherein an author of the knowledge tip is allowed to modify content of the knowledge tip, and wherein the author is a member of the organization responsible for providing the existing knowledge tip to the tips repository.

10. The method of claim 1 wherein receiving the knowledge tip in the tips repository further comprises: a. creating a new category in the tips repository if a required category does not exist among a plurality of predefined categories in the tips repository; and b. storing the knowledge tip to the new category.

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22. The apparatus of claim 20 , wherein the one or more processors are further configured to perform the determining steps multiple times in order to modify the value associated with the value metric.

20. An apparatus for enabling interoperability between a plurality of participants in a network, the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured: to determine a value associated with a value metric defined for at least a portion of the network; to determine two or more alternative information flows between two or more of the plurality of participants in the network based at least in part on one or more semantic models corresponding to the plurality of participants and on the value associated with the value metric, wherein the one or more semantic models define inputs, outputs, and functionality for each of the plurality of participants and define at least a portion of information produced or consumed by the plurality of participants; and to optimize an overall value of the network by selecting combinations of said alternative information flows for at least one portion of the network in order to satisfy consumers of information.

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3. The method of claim 1 , wherein: the GROUP BY clause in the outer query is a first GROUP BY clause that references one or more columns; the subquery includes a second GROUP BY clause that references one or more columns; the one or more columns referenced in the first GROUP BY clause includes the one or more columns referenced in the second GROUP BY clause; and generating the transformed query further comprises the steps of: creating a second inline view; wherein: the inline view is a first inline view; the first inline view is nested within the second inline view; the algebraic aggregate window function includes a partition-by clause that references the one or more columns references in the second GROUP BY clause; and the predicate in the outer query that references the first inline view also references the second inline view.

11. The method of claim 3 , wherein: the HAVING clause specifies that an ANY function be applied to the subquery; the HAVING clause specifies that an expression be equal to the ANY function; the second inline view includes a COUNT function, wherein the COUNT function counts how many rows in a set of results for the subquery are equal to the expression; and the predicate in the outer query references the output of the COUNT function.

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4. The method of claim 1 , wherein the step of generating a context data query further comprises: extracting a key word from the collected context data; and combining the extracted key word and the path record to generate the context data query.

1. A method for recording context data for an online application, comprising: displaying a context data user interface to a user accessing a page in the online application, the context data user interface comprising a first input element configured to receive a request from the user to designate a page as an initial page, further comprising a second input element configured to receive a request from the user to designate a page as an end page, and further comprising a query input element configured to receive a query from the user; receiving, from the user through the first input element of the context data user interface, the request that said online application designate said page as the initial page; designating, in response to said request for initial page designation, said page as the initial page of a plurality of pages accessed by the user; initiating, in response to said initial page designation, the collection of context data for each of the plurality of pages accessed by said user, wherein the context data is a page identifier unique to each page; collecting context data relating to the plurality of pages accessed by said user, wherein said plurality of pages comprises at least said initial page, an intermediary page accessed by said user, and last page accessed by said user, and further wherein the plurality of pages accessed by the user are not pre-selected by said user; receiving, from the user through the context data user interface, an express request that said online application designate said last page as the end page, wherein said request comprises a selection by the user via the second input element of the context data user interface; designating, in response to said express request for end page designation, said last page as the end page; ending, only in response to said end page designation, the collection of context data; generating, in response to ending the collection of context data, a step-by-step path record using the unique page identifier of each of said plurality of accessed pages; generating a context data record comprising the collected context data and the generated path record; storing the context data record in a non-transitory storage medium; generating, before receiving a context data query from the user, a context data query term, wherein said context data query term is based on the generated context data record; storing the generated context data query term in a non-transitory storage medium; receiving from the user a context data query, wherein the context data query comprises a context data query term; querying the stored context data record using the context data query; and displaying a result of the context data query to the user, if a result is returned by the context data query.

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23. A non-transitory computer-readable recording medium storing a program to cause a computer to implement the method of claim 17 .

17. A virtual world processing method comprising: encoding information relating to sensor capability into first metadata based on predetermined representation syntax, wherein the predetermined representation syntax defines attributes and flags corresponding to the attributes, and wherein the first metadata includes the flags corresponding to the attributes, and at least one attribute corresponding to at least one flag having a predefined logic value; encoding information relating to a virtual world into second metadata, wherein the information relating to the virtual world comprises a virtual world object characteristic; generating information that is applied to the virtual world, based on the first metadata and the second metadata; and encoding the generated information into third metadata.

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33. The system of claim 25 , where selecting an application includes using one or more selection rules to select an application based on the context information.

25. A system comprising: a processor; and a memory for storing instructions, which when executed by the processor, causes the processor to perform operations comprising: receiving a request to open a file, the file having a file type, where the file type identifies a distinct data format of data in files of the file type; launching a default application for opening files of the file type; running the default application to identify a plurality of applications in the computing environment that are capable of opening files of the file type, each application in the plurality of applications being associated with the file type based on the file type and file association data; using the default application to select an application from the plurality of identified applications, the selection of the application being based at least in part on context information; and launching the selected application to open the file where the action to open the file is dependent on the file type.

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7. A computer program product for selecting strangers for information spreading on a social network, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a processor to: train statistical models with history data of the information spreading of strangers on the social network, the strangers on the social network being not known to a requester who requests the strangers on the social network to conduct the information spreading; compute information spreading probabilities based on features of the strangers on the social network; compute information reach of the strangers on the social network; compute information spreading probabilities based on a wait time of the strangers on the social network, the wait time being a period of time for the strangers on the social network to initiate information spreading in response to being requested by the requester; compute fitness scores of the strangers on the social network, the fitness scores being a function of the information spreading probabilities based on features, the information reach, and the information spreading probabilities based on the wait time; rank the strangers on the social network in a sorted set, based on the fitness scores; select one or more of the strangers for the information spreading from the sorted set; and wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of minimizing time for the information spreading within a confidence probability.

11. The computer program product of claim 7 , the computer program product further comprising the program code executable by the processor to: determine a first set for subset selection, the first set including a portion of the strangers on the social network; rank the first set based on the fitness scores; compute a value of an optimization objective function for each of intervals in the first set; determine an interval in the first set, the interval in the first set having an optimal value of the optimization objective function; determine a second set for selecting the one or more of the strangers for the information spreading; rank the second set based on the fitness score; and program instructions to determine an interval in the second set, the interval in the second set being defined by the interval in the first set, based on percentiles.

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1. An information handling system, comprising: one or more processing devices configured to execute a network management system (NMS) that includes an ontology-based command line interface (CLI) knowledge model; where the one or more processing devices of the information handling system are configured to be communicatively-coupled across a network to one or more network devices of a networking system; where the one or more processing devices are configured to execute the NMS to maintain and administer the networking system using the ontology-based CLI knowledge model; where the ontology-based CLI knowledge model comprises an ontology build module, the one or more processing devices configured to execute the ontology build module as one or more ontology build steps that comprise: a seed learning step where build parameter information is received by the ontology build module, a learning and knowledge building step for CLI command structure and network device behavior where each given one of the network devices is interrogated over the network to elicit and receive a response from the given network device describing one or more of the CLI characteristics it possesses, and a CLI knowledge model creation step where the one or more CLI characteristics received from each given network device is organized as CLI data to create a CLI knowledge model; and where the ontology-based CLI knowledge model further comprises an ontology implementation module, the one or more processing devices configured to execute the ontology implementation module as ontology implementation steps that comprise: a NMS deployment step where the ontology-based CLI knowledge model is bound to one or more NMS functions, and a dynamic graphical user interface (GUI) creation step where a GUI is created at runtime based on the created CLI knowledge model.

3. The information handling system of claim 1 , where the information handling system further comprises at least one display device; and where the one or more processing devices are configured to execute the ontology implementation module as ontology implementation steps that comprise: presenting the created runtime GUI on the display device, the presented runtime GUI comprising at least first and second interface windows; where the first interface window comprises a write interface window that comprises a configuration tree and input interface for writing information to a given network device, the write interface allowing a user of the information handling system to make selections, and the ontology implementation module using the created CLI knowledge model to generate CLI commands to a given network device based on one or more of the user selections; and where the second interface window comprises a read back interface window that comprises a configuration tree and interface for reading CLI response information back from the same given network device that is written to by interface window, the ontology implementation module dynamically constructing the runtime read back interface window using the created CLI knowledge model to map components of the read back interface window to the created CLI knowledge model output. where the first interface window and second interface window enable the user to edit the CLI command phrase and check the CLI syntax of the edited command phrase using the CLI knowledge model.

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26. A computer-based method of obtaining solution suggestions for problems, using an electronic model of a system or process, wherein the electronic model includes components of the system or process and relationships between the components, said method comprising the following computer executed steps: analyzing the components and the relationships between the components of the electronic model, including identifying a problem to be solved; generating a machine representation of the problem; reformulating the machine representation into a natural language or Boolean query; automatically submitting the query to at least one knowledge base having solutions stored therein; and returning a set of solution suggestions responsive to the query from the at least one knowledge base.

27. The method of claim 26 , further comprising presenting the set of solution suggestions via an output device.

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8. The system of claim 1 wherein the processor is further adapted for receiving user input for test executing the generated SQL query for displaying a query search result value.

1. A system for computer application code automation, the system comprising: a code automation computer server configured for presenting an electronic user interface for receiving user input for generating a Structured Query Language (SQL) query, the user input comprising a plurality of SQL tokens; a processor, associated with the code automation computer server, for receiving the plurality of SQL tokens, the processor retrieving from memory and executing computer executable instructions for: displaying a first electronic user interface screen for accepting a first partial portion of the user input comprising the plurality of SQL tokens, performing a check to identify a possible error or a query performance problem based on the first partial portion of the user input, displaying a warning screen when the first partial portion of the user input is associated with a possible error or a query performance problem; and displaying a second electronic user interface screen for accepting a second partial portion of the user input comprising the plurality of SQL tokens, wherein the second electronic user interface screen is displayed after displaying the warning screen; wherein the processor is adapted for automatically incorporating the generated SQL query into the computer application code and storing the computer application code in a non-transitory computer readable medium.

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18. The storage of claim 10 , wherein the compiled graphical model is free of violations of the coding standard.

10. A storage for holding computer-executable instructions, the instructions comprising instructions for: providing a coding standard in a graphical modeling environment; applying the coding standard to at least a portion of a graphical model in the graphical modeling environment to detect a violating segment of the graphical model that violates the coding standard; displaying the violating segment of the graphical model differently than a non-violating segment of the graphical model; displaying information on violation of the coding standard associated with the violating segment of the graphical model automatically generating a coding standard compliant intermediate representation of the graphical model; compiling the graphical model for execution using the coding standard compliant intermediate representation of the graphical model; and generating code for the compiled graphical model.

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1. An external medical device, comprising: a housing; an energy storage module within the housing for storing an electrical charge; a defibrillation port for guiding via electrodes the stored electrical charge to a person; a user interface structured to deliver prompts to a user during a defibrillation session; and a language detector in the housing structured to determine a vicinity language, in which the prompts delivered by the user interface to the user during the defibrillation session are in a language that is selected based on the determined vicinity language, and further in which the language detector includes an optical character recognition (OCR) module, or both a voice recognition module and an OCR module.

3. The device of claim 1 , in which the prompts include one or more audible prompts, one or more visible prompts, or a combination of one or more audible prompts and one or more visible prompts.

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16. A method for transforming media elements into a narrative comprising: receiving, with a clustering module in communication with a processor and a memory, a dataset comprising a plurality of media elements each comprising metadata; organizing, with the clustering module, the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and creating, with a narrative module in communication with the processor and the memory, a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result: T>SI+GI+TI+P min +SE guess .

23. The method of claim 16 , further comprising: receiving, with a user interface (UI) module in communication with the processor and the memory, at least one edit to the narrative sequence; causing, with the UI module, the narrative sequence to be displayed; receiving, with the UI module, at least one filter selection and select the dataset from a set of media elements by applying the at least one filter to the plurality of data elements; or a combination thereof.

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7. A computing device comprising: a processor; and a data storage device storing instructions executable by the processor, cause the processor to: receive a query domain name; provide the query domain name as input to a predictive model that has been trained to determine whether the query domain name is an algorithmically generated domain name, wherein: the determination is based on syntactic features of the query domain name; and the syntactic features include a count of impossible character n-grams included in at least a portion of the query domain name, where n is a positive integer greater than one; and receive, as output from the predictive model, data indicating whether the query domain name is algorithmically generated.

8. The computing device of claim 7 , further comprising instructions executable by the processor to: provide the query domain name as input to a second predictive model that has been trained to determine whether the query domain name was generated by a particular domain name generation algorithm, wherein the determination is based on at least one of the syntactic features of the query domain name; and receive, as output from the second predictive model, data indicating whether the query domain name was generated by the particular domain name generation algorithm.

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1. A method of providing an in-page search of contents of a webpage, the method comprising: displaying, with a web browser, a visible portion of a webpage, the webpage comprising: markup text comprising text and formatting tags that format the text according to a markup language; executable code that performs an in-page search of contents of the webpage, the executable code being independent of search functionality of the web browser and included in the markup text; and an element that receives a user's search criteria; reading the user's search criteria with the executable code; searching contents of the webpage with the executable code to identify text matching the search criteria; providing on the webpage, with the executable code, a set of user interface controls for the user to select text formatting options for text identified as matching the search criteria; modifying, with the executable code, a set of markup tags corresponding to the identified text in accordance with the text formatting options selected by the user, based on a determination that the identified text matches the search criteria, to change the appearance of the identified text relative to other text on the webpage, wherein the modified set of markup tags make the identified text a hyperlink allowing the user to jump to a next match on the webpage, wherein modifying the set of markup tags corresponding to the identified text comprises: removing the identified text from the webpage using the executable code; adding formatting instructions in front of and behind the removed identified text using the executable code; and reinserting the removed identified text and the added formatting instructions into the webpage at an original location of the removed identified text; and redisplaying, with the executable code, the visible portion of the webpage with the modified set of markup tags.

5. The method of claim 1 , wherein the element of the webpage comprises a search box.

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9. A system, comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution causes the data processing apparatus to perform operations comprising: accessing a plurality of queries; for each query of the plurality of queries: determining a first number of occurrences of the query for which the query was received for unfiltered search operations, each unfiltered search operation being a search operation for which search results for resources including content of a first type can be returned in response to the query; determining a second number of occurrences of the query for which the query was received for filtered search operations, each filtered search operation being a search operation for which search results for resources including the content of the first type cannot be returned in response to the query; determining a total number of unfiltered search operations based on the first numbers of occurrences of the plurality of queries; determining a total number of filtered search operations based on the second numbers of occurrences of the plurality of queries; for each query of the plurality of queries: determining a first value based on a ratio of the first number of occurrences for of the query to the total number of unfiltered search operations; determining a second value based on a ratio of the second number of occurrences for of the query to the total number of filtered search operations; and determining a first content type value based on a ratio of the first value to the second value; for each query of the plurality of queries having a first content type value that meets a first threshold, classifying the query as a first content type seeking query, the classification being indicative of likely user interest in content of the first type; and for each query of the plurality of queries having a first content type value that does not meet the first threshold, classifying the query as a first content type independent query, the classification being indicative of unlikely user interest of content of the first type.

13. The system of claim 9 , wherein determining the second number of occurrences comprises: determining that, during a search session for a client device, a query was first received for a filtered search operation and then received for an unfiltered search operation, and in response: discounting the first reception of the query for the filtered search operation from the second number of occurrences.

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1. A method for recommending user actions for data analysis, the method comprising: storing, by a multi-tenant system, data received from a plurality of external systems, each external system associated with a customer of the multi-tenant system, each customer associated with one or more users; monitoring, by the multi-tenant system, user interactions performed by users of the multi-tenant system with reports, the monitoring comprising associating a user interaction with a context in which the user interaction is performed, the context identifying at least a report with which the user interaction was performed; performing, by the multi-tenant system, a sequence of interactions with the user, the performing of each interaction comprising: determining a recommendation comprising a potential sequence of computer-executable actions based on past user interactions performed by users of the multi-tenant system in contexts matching a context of the user, the matching contexts comprising sequences of the past user interactions, wherein the context of the user comprises a present sequence of user interactions performed by the user; determining a recommendation score for the recommendation, wherein determining the recommendation score comprises determining an aggregate value based on the past user interactions; responsive to determining the recommendation score for the recommendation, constructing a computer-actionable widget for the recommendation based on the recommendation score, and configuring a user interface comprising the computer-actionable widget, the widget comprising a compiled graphical user interface element configured to receive one or more user interactions associated with the recommendation and automatically execute the recommended sequence of potential computer-executable actions, the configuring of the user interface comprising: determining a value of an attribute of the widget based on the recommendation score of the recommendation associated with the widget, the attribute specifying one of: a size of the widget; a size of text associated with the widget; or an appearance of the widget; and configuring the computer-actionable widget, comprising, performing at least one of: scaling the size of the widget according to the determined value of the attribute; scaling the size of the text associated with the widget according to the determined value of the attribute; or configuring the appearance of the widget according to the determined value of the attribute; and receiving an interaction from the user based on the computer-actionable widget of the user interface.

2. The method of claim 1 , wherein the recommendation score for the recommendation is determined based on factors including a number of times interactions matching the user interaction were performed by users in the past for a matching context.

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1. A computer-implemented method for processing query data comprising: receiving, from a client over a network a portion of a query, wherein the portion of the query is not formerly issued by the user that initiated the query; before any predicted queries are provided to the client and in response to receiving the portion of the query determining, based on the portion of the query, a set of one or more predicted queries that correspond to the portion of the query; selecting, based upon selection criteria, a particular predicted query from the set of one or more predicted queries; processing the particular predicted query to obtain search results; and providing both the set of one or more predicted queries and the search results to the client over the network; wherein determining the set of one or more predicted queries includes: determining a plurality of potential predicted queries; for each query of the plurality of potential predicted queries: searching a first database to determine a first value that indicates how often said each query was issued during a first period of time; searching a second database to determine a second value that indicates how often said each query was issued during a second period of time that occurred temporally before or after the first period of time; scaling the first value by a scale factor to generate a scaled value: generating a resulting value based on the scaled value and the second value; and associating the resulting value with said each query: and using the resulting value of each query of the plurality of potential predicted queries to determine the set of one or more queries from the plurality of potential predicted queries.

10. The computer-implemented method of claim 1 , further comprising: receiving an indication of a selection of another predicted query in the set of one or more predicted queries; and providing new search results based on the selection of the selected predicted query.

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4. The touch-typable device as claimed in claim 3 , wherein said user accesses a second set of said textual input choices on said movable keymask from said set of likely and valid input choices using said text input keypad of said touch-typable device in case said desired textual input is not present in said textual input choices.

3. The touch-typable device as claimed in claim 1 , wherein said touch-typable device includes said display that is a touch-screen, and wherein said desired textual input choices are directly accessible through and dynamically assignable to said plurality of touch-screen enabled cells of said movable keymask.

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17. The non-transitory machine readable medium of claim 16 , further comprising selecting the context from a plurality of contexts based on a relevance of the context to the member in comparison to a relevance of an additional context of the plurality of contexts to the member.

18. The non-transitory machine readable medium of claim 17 , wherein the selecting the context from the plurality of contexts is further based on information specified by the member in a profile of the member.

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36. A system for measuring the distinctiveness of a result generated from a collection of information, wherein the result is comprised of elements associated with the collection of information, the system comprising: an analysis component adapted to automatically obtain a statistical distribution of at least one identifying characteristic within a result; a measurement component adapted to generate a measurement of distinctiveness for the result based on the statistical distribution of the at least one identifying characteristic; and a comparison component adapted to compare the measured statistical distribution against a baseline statistical distribution, wherein the comparison component is further adapted to determine that the compared statistical distribution exceeds a threshold for distinctiveness.

48. The system according to claim 36 , wherein the collection of information comprises a collection of at least one document, and wherein the at least one document further comprises a unit of storage of digital data.

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5. The method of claim 1 , automatically identifying the intention metadata comprising examining the body for a natural language indicator.

1. A computer-based method, comprising: automatically identifying intention metadata associated with an attachment to an email based upon at least one of a body of the email or a header of the email, where the attachment comprises a text-based file or an image file and where the intention metadata indicates a sender intention for presentation of the attachment with a first portion of the attachment comprising a first portion of the text-based file or a first portion of the image file highlighted and with a second portion of the attachment comprising a second portion of the text-based file or a second portion of the image file highlighted; and applying the intention metadata to the attachment such that a recipient can identify the sender intention for the attachment, applying the intention metadata comprising applying the intention metadata to the attachment such that the sender intention for the attachment is displayed in the body of the email.

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2. The method of claim 1 , said method further comprising: prior to said generating, parsing, by the one or more processors, each program statement in the first computer program to generate the parsed first computer program.

6. The method of claim 2 , wherein said parsing parses the whole first computer program completely without halting said parsing and without throwing any exception even though the first computer program includes the first error, and wherein said translating translates the whole parsed first computer program completely without halting said translating and without throwing any exception even though the parsed first computer program includes the second error.

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6. The system for automated password generation in a data processing system according to claim 5 , further including means for storing a copy of each randomly generated password within said memory.

5. A system for automated password generation, said system comprising: memory for storing a known valid multi-character password string for a target data processing system; means for automatically determining a character type for each character in said known valid multi-character password string; means for automatically assigning a random character of identical type to replace each character in said known valid multi-character password string to create a randomly generated password, which will comply with specified password rules, and syntax for said target data processing system; means for submitting said randomly generated password to said target data processing system; and means for generating an alert message in the event said randomly generated password is rejected by said target data proceeding system “N” times; and means for permitting a user to define “N”.

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9. A method for automatically adding process nodes to print production workflows by inferring knowledge from asset metadata tags and using said knowledge during process network generation, comprising: providing a print product description; extracting asset metadata from a plurality of resources associated with said print product description; processing said asset metadata through an automated reasoning system to infer predefined characteristics from said asset metadata to form inferred metadata; and utilizing said inferred metadata to add and parameterize a process node to a process network.

14. The method of claim 9 , wherein said automated reasoning system further comprises a knowledge-base for adding said process node to said process network.

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1. A method for dynamically generating search results from a dataset, the method comprising: receiving a first search keyword from a user; searching for a first content object in the dataset using the first search keyword, the first content object having first metadata portion separate from and associated with a first audiovisual portion of the first content object; identifying the first content object in the dataset using the first search keyword; displaying the first content object as the search results; retrieving the first metadata associated with the first audiovisual portion of the first content object; building a metadata pool using the first metadata associated with the first audiovisual portion of the first content object; selecting a second search keyword from the metadata pool; searching for a second content object in the dataset using the second search keyword, the second content object having second metadata portion separate from and associated with a second audiovisual portion of the second content object; identifying the second content object in the dataset using the second search keyword; displaying the second content object as the search results; retrieving the second metadata associated with the second audiovisual portion of the second content object; and building the metadata pool using the second metadata associated with the second audiovisual portion of the second content object; wherein the displaying the first content object as the search results includes displaying the first search keyword in conjunction with a first visual object indicative of the first audiovisual portion, and wherein the displaying the second content object as the search results includes displaying the second search keyword in conjunction with a second visual object indicative of the second audiovisual portion.

3. The method of claim 1 , wherein the building the metadata pool using the second metadata includes replacing the first metadata in the metadata pool having the first metadata with the second metadata.

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1. A method for inserting and reusing document parts in an electronic document created within a word processing application program, comprising: receiving a selection of a document part category; displaying a gallery of document parts associated with the selected document part category, wherein the document parts include reusable portions of document content; receiving a selection of a document part from the gallery, wherein the document part includes a role identifier that indicates a role of the document part within the electronic document; identifying the role indicated by the role identifier; inserting the selected document part in the electronic document in accordance with the identified role; receiving user data; and modifying the selected part with the received user data, wherein modifying the selected document part with the received user data comprises adding additional data to the selected document part, the additional data comprising at least one document part from one or more alternative galleries of document parts and selecting an option from a menu comprising a plurality of options for modifying the selected document part, wherein selecting the option from the menu for modifying the selected document part comprises generating a submenu displaying thumbnails of additional document parts from the gallery and an option for removing a currently displayed document part, and wherein the submenu is utilized to replace a currently displayed document part with one of the additional document parts from the gallery without returning to the gallery.

5. The method of claim 1 , wherein the gallery of document parts defines a page layout for the electronic document.

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11. The system of claim 1 , wherein the feedback comprises a lack of an input from a user of the system within a threshold period of time.

1. An online learning dialog system comprising: one or more processing units; memory communicatively coupled to the one or more processing units, the memory having stored instructions that, when executed by the one or more processing units, configure the online learning dialog system to implement: a speech model that receives a speech input and provides speech events; a decision engine model that receives the speech events from the speech model and selects an action based, at least in part, upon a probability distribution, the probability distribution being associated with uncertainty regarding a plurality of parameters of the decision engine model applied to the speech input, wherein the probability distribution is: defined by an influence diagram that is configured to maximize long term expected utility and apply the Thompson strategy; and expressed as: p ⁡ ( U , V ⁢ | ⁢ D , Θ ) = ∏ X ∈ U ⋃ V ⁢ p ⁡ ( X ⁢ | ⁢ Pa ⁡ ( X ) , Θ X ) where U denotes chance variables, D denotes decision variables, and V denotes value variables; where Pa(X) denotes a set of parents for node X; and where Θ X denotes a subset of parameters related to the applied speech input in Θ that define local distribution of X; and, a learning component that in an online manner modifies at least one of the parameters of the decision engine model based upon feedback associated with the selected action, wherein the feedback comprises a lack of verbal input from a user of the system or an environment within a predefined period of time.

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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.

14. The method of claim 1 , further comprising: providing a display including a list of selectable validation rules associated with the entity type classification from which the validation rule is selected.

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16. The computer program code as claimed in claim 12 , wherein the method further comprises: formatting each corresponding character based on their respective assigned weighting factors for collectively displaying each of the corresponding characters as a word having characters of differing font sizes.

17. The computer program code as claimed in claim 16 , wherein the formatting further comprises: formatting each corresponding character along a horizontal alignment whereby a horizontal alignment takes place in an upper quartile of each of the corresponding characters.

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12. A computing system, comprising: a storage element operable to store a representation of an application source code; and a processor operable to perform operations including: specifying a plurality of runtime binding rules, each runtime binding rule of the plurality of runtime binding rules configured to augment the representation of the application source code using code slicing techniques, each runtime binding rule of the plurality of runtime binding rules associated with one or more locations within the representation of the application source code, at least one runtime binding rule of the plurality of runtime binding rules associated with a method invocation and a concrete implementation and specifying that the concrete implementation be visited either before or after the method invocation, the concrete implementation is visited before the method invocation when a first location of the one or more locations is before the method innovation and the concrete implementation is visited after the method invocation when a second location of the one or more locations is after the method innovation; beginning to traverse the representation of the application source code; monitoring a history of the traverse; continuing to traverse the representation of the application source code based on the history of the traverse, wherein continuing to traverse the representation of the application source code includes identifying a plurality of concrete implementations of a method invocation and traversing less than all of the concrete implementations based at least in part on one or more of the plurality of runtime binding rules, the concrete implementations being traversed being selected based at least in part on the history of the traverse, and updating the history of the traverse; and providing a set of identified vulnerabilities, the set of identified vulnerabilities based at least in part on the history of the traverse.

14. The computing system of claim 12 , wherein monitoring a history of the traverse includes storing metadata associated with visited concrete implementations of method invocations.

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6. A typewriter according to claim 5, wherein a combination of said letters of a first one of said words, in a plurality of consecutive ones of said words each of which has said combination of letters, are represented by the character codes in place of said special code.

5. A typewriter according to claim 4, wherein said word data is stored in the respective one of said word-data memory locations of the addressed data memory locations such that first letters of the individual words contained in the dictionary are arranged in a predetermined order of presentation of letters used in said language, second letters of the words being arranged in said predetermined order when said first letters of the adjacent words are identical, third and following letters if any of the words being arranged in said predetermined order when said second and following letters of said adjacent words are identical, said special code being used to represent plural consecutive letters of the word as counted from the first letter thereof when said plural consecutive letters are identical with corresponding letters of an adjacent word.

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4. The method according to claim 3 , wherein the setting the destination includes: searching at least one Point Of Interest (POI) from a Point Of Interest database (POI database) using the place-associated information detected by analyzing the text; and establishing the destination in response to a search result of the POI database.

3. The method according to claim 1 , wherein the setting the place obtained on the basis of the place-associated information to the destination includes: detecting the place-associated information by allowing the navigation device to analyze the text; and setting a destination using the detected place-associated information.

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18. The system of claim 15 , wherein determining a context of the video-content object comprises one or more of: recognizing a physical object; identifying a particular physical object; detecting a physical object; tracking a physical object; recognizing a pose; recognizing a face; determining a topic; recognizing a scene; recognizing an activity; or recognizing behavior.

15. A system comprising: one or more processors; and a memory coupled to the processors and comprising instructions operable when executed by the processors to cause the processors to: access a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; access a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; access a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; determine a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and determine a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object.

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9. A non-transitory computer program product for communication monitoring based on sentiment, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to monitor a new communication prior to sending created by a sender to a recipient, wherein the new communication comprises text input by the sender; program instructions to analyze the text of the new communication using sentiment analysis and program instructions to determine a sentiment score on a scale between negative sentiment and positive sentiment; program instructions to reference an overall relationship score based on past communications between the sender and the recipient in response to the sentiment score for the text of the new communication being on a negative side of a first predefined threshold on the scale; program instructions to hold a transmission of the new communication or activating another action in response to the overall relationship score being on the negative side of a second predefined threshold in response to the overall relationship score being on the negative side of a second predefined threshold; and program instructions to send a notification to at least one of the sender or a supervisor of the sender in response to the overall relationship score being on the negative side of the second predefined threshold.

13. The computer program product as claimed in claim 9 , wherein multiple communication channel sources comprise sources from a group of: email communication channels, instant messaging communication channels, short message service communication channels, social media network communication channels, online forum channels, and other forms of communication channels sent from a computing device or mobile communication device.

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28. The apparatus of claim 27 wherein the interface comprises a user interface, and wherein the received input comprises user input.

27. An apparatus comprising: a processor configured to: define a communication goal data structure, wherein the communication goal data structure is associated with a communication goal and comprises (1) first data that is indicative of a content block data structure associated with the communication goal data structure, the associated content block data structure comprising a parameterized model for a plurality of data components that need to be analyzed to generate a narrative and a parameterized model for a plurality of computational components for analyzing the data components to generate a narrative, and (2) second data that is indicative of a plurality of communication goal parameters whose values are variable, wherein the plurality of communication goal parameters are for use by the parameterized models of the associated content block data structure; store the defined communication goal data structure in a memory such that the defined communication goal data structure is accessible for use by a processor when automatically generating a narrative about data based on input about a communication goal to be satisfied by the automatically generated narrative; receive input through an interface, the input defining a plurality of values for the communication goal parameters; instantiate the content block data structure associated with the communication goal data structure based on the defined parameter values; and automatically generate a narrative about the data using the instantiated content block data structure, wherein the narrative targets the communication goal associated with the communication goal data structure.

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4. The medium of claim 3 wherein the second network location is identified by a second identifier.

3. The medium of claim 2 wherein the translated content that satisfies the search query is included in at least a portion of a second network location of the one or more network locations.

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7. The method of claim 1 , wherein steps (b) and (c) more specifically comprise: overlaying a grid of shapes comprising negative space and nested shapes comprising positive space onto the glyph; and removing shapes on the grid that lie entirely outside, or partially on, the outline of the glyph.

1. A method for using at least one computer having a memory containing a font and a processor adapted to execute computer-executable instructions, to generate a print compound conserving font having at least one glyph comprising positive space defining an outline of the glyph against a background of negative space, the method comprising, for at least one glyph in the font in the memory of the computer: (a) retrieving the glyph from the memory; (b) adding at least one shape comprising negative space to the glyph, within the outline of the glyph; (c) adding at least one shape comprising positive space within at least one shape comprising negative space, the at least one shape comprising positive space having a smaller size than the corresponding shape comprising negative space; and (d) storing the glyph in the computer memory.

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9. A computer program product tangibly embodied in a non-transitory machine-readable storage device for adapting an Eclipse development environment to an advanced business application programming (ABAP) language, the computer program product comprising instructions to implement: a first component to enable the Eclipse development environment to recognize the ABAP language and perform syntax checking for the ABAP language in the Eclipse development environment; and a second component to provide access to a library of objects from the Eclipse development environment.

11. The computer program product of claim 9 , wherein the library of objects is stored in a repository that is separate from a device on which the Eclipse development environment is executed.

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22. The system of claim 18 , wherein the operations further comprise: identifying a search result access log identifying search queries and corresponding snippets, each record in the search result access log identifying a respective stored search query and a corresponding snippet, the snippet of a respective stored search query being a portion of content from a document accessed by a user, the document having been presented to the user as a search result in response to receiving the respective stored search query; and building a translation model trained on the search queries and the corresponding snippets including using the search queries from the search result access log as a source language for the translation model and the corresponding snippets as a target language for the translation model, wherein using statistical machine translation to translate the initial search query into a translated search query comprises providing the initial search query as input to the translation model trained on the search queries and the corresponding snippets and receiving the translated search query as output from the translation model trained on the search queries and the corresponding snippets.

18. A system comprising: one or more computers; and a computer-readable storage device having stored thereon instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving an initial search query including one or more terms; using statistical machine translation to translate the initial search query into a translated search query, the translated search query being different from the initial search query and being in a same natural language as the initial search query; identifying a first term occurring in the initial search query that was replaced by a corresponding second term occurring in the translated search query; determining that one or more context terms that occur adjacent to the first term in the initial search query also occur adjacent to the second term in the translated search query; and in response to determining that one or more context terms occurring adjacent to the first term in the initial search query also occur adjacent to the second term in the translated search query, designating the second term as a synonym of the first term when the first term occurs adjacent to the one or more context terms in search queries, wherein a search engine expands a particular search query to include the second term in response to a determination that the first term occurs adjacent to the one or more context terms in the particular search query.

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18. The method of claim 10 , wherein the first audio content includes dialog in a user selected language.

10. A method for use with a system including a plurality of speakers, a memory, and a processor, the method comprising: playing a movie having a first audio content for a movie in a first language and a second audio content for the movie in a second language different than the first language; obtaining, using the processor, a first position of a first user of a first user device with respect to each of the plurality of speakers; obtaining, using the processor, a second position of a second user of a second user device with respect to each of the plurality of speakers; playing, during the playing of the movie and using first one or more of the plurality of speakers, the first audio content for the movie in the first language, based on the first position of the first user of the first user device with respect to each of the plurality of speakers; and playing, during the playing of the movie and using second one or more of the plurality of speakers, the second audio content for the movie in the second language, based on the second position of the second user of the second user device with respect to each of the plurality of speakers.

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12. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods; wherein the invoking of the producer, converter, and distributor methods is triggered by at least one of the following: a schedule, a user input, and an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the schedule, the user input, or the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the schedule, the user input, or the event meets a predefined criterion.

20. The method of claim 12 , wherein the converted document distributed through the distribution channel is at least one selected from the group consisting of: an electronic message, an item for display in a portal, and combinations thereof.

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16. A non-transitory computer-readable storage medium of claim 15 , wherein to construct the decision diagram, the apparatus is caused to further perform: serialize the resource description framework graph into variables of a predetermined format; determine a bit size of the variables by calculating sizes of the variables or using a fixed size; and construct a representation of the reduced ordered binary decision diagram from the variables.

15. A non-transitory computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least the following steps: construct a reduced ordered binary decision diagram from a resource description framework graph; compute a hash identifier corresponding to the decision diagram; and cause, at least in part, a storing of the hash identifier with the decision diagram.

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29. The method of claim 1 , wherein receiving at least one query includes receiving at least one query seeking production log data.

1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user.

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23. A process for enabling a performer to control the production of at least a first musical accompaniment and a second musical accompaniment including notes having an instrumentation pattern, said process comprising the steps of: storing a first plurality of music signals defining at least in part the first musical accompaniment and a second plurality of music signals defining at least in part the second musical accompaniment; enabling the performer during the performance to select one of said first and second musical accompaniments; enabling the performer to select at least one harmony from a plurality of different harmonies; generating parameter signals in response to the selection of the one musical accompaniment and one harmony, said parameter signals defining a first segment of music including a plurality of pitched accompaniment notes arranged in the one harmony and having a first instrumentation pattern; modifying the parameter signals in response to a change in the selected musical accompaniment while retaining the one harmony during the performance in order to generate parameter signals defining a second segment of music having a second instrumentation pattern different from the first instrumentation pattern; and converting the parameter signals to sound, whereby a performer of limited skill or musical knowledge can play a musically variable accompaniment to a melody written in any one of a variety of musical keys.

44. A process, as claimed in claim 23, wherein the predetermined harmony comprises a predetermined chord type based on a predetermined root, wherein the plurality of harmonies comprises a plurality of chord types and a plurality of roots, and wherein the step of generating a harmony signal comprises the steps of: generating a chord type signal representing the predetermined chord type; and generating a root signal representing the predetermined root.

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15. The computer-implemented method of claim 1 , further comprising weighting the edges of the graph based on one or more weighting factors, wherein the weighted edges affect how much the label values are iteratively propagated in the graph.

1. A computer-implemented method comprising: receiving, at a computer system, a request to identify interests for users of a social network; accessing, by the computer system, a graph that includes i) nodes that represent at least a portion of the users of the social network and ii) edges that connect the nodes and that represent relationships among the portion of the users of the social network; assigning labels to at least some of the nodes of the graph based, at least in part, on content that is associated with the portion of the users on the social network, wherein the labels correspond to topics of user interest; determining, for the at least some of the nodes, label values for the assigned labels based, at least in part, on content that is associated with users that correspond to the at least some of the nodes, wherein the label values determined for the at least some of the nodes and the assigned labels indicate degrees to which the users represented by the at least some of the nodes are interested in the topics that correspond to the assigned labels, wherein a first label value for a first label and a second level value for a second label are determined for a first node and a second label value for the second label is determined for a second node, the first node and the second node having an indirect connection between each other that comprises a portion of the edges and one or more other nodes; iteratively propagating, for at least a threshold number of iterations, the label values in the graph based on the nodes and the edges of the graph, the iterative propagation causing at least a portion of the second label value for the second node to be propagated from the second node to the first node through the indirect connection between the first and second nodes, wherein propagation of the at least a portion of the second label value for the second node causes the first label value for the first node to decrease or the second label value for the first node to increase, or both; and providing, by the computer system, the determined label values for the nodes that result from the iterative propagation.

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9. The error-detecting method for a Chinese article as claimed in claim 8 , further comprising: acquiring one of the second correct Chinese character strings when the Chinese sentence comprises the acquired context; and setting the acquired second correct Chinese character string as the second candidate term.

8. The error-detecting method for a Chinese article as claimed in claim 7 , further comprising: acquiring the second erroneous index that is the same as the second erroneous Chinese character string, and one of the contexts according to the acquired second erroneous index; and determining whether the Chinese sentence comprises the acquired context.

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3. The system of claim 1 , wherein the annotations comprise rich media.

1. A collaborative computing data processing system comprising: a collaborative computing environment executing in a memory of a server formed between different collaborative computing clients, the collaborative computing environment comprising a plurality of collaborative objects; a collaborative information structure document (ISD) stored in the server as a collaborative object, the collaborative ISD comprising an object section and a separate annotations section, the object section encapsulating collaborative objects and also references to the collaborative objects in the collaborative computing environment, the annotations section encapsulating annotations to the collaborative ISD; and, a collaborative ISD interface executing in the memory of the server, the collaborative ISD interface providing access to add objects to at least one of the object section of the collaborative ISD and the annotations section of the collaborative ISD and also providing access to add annotations to the annotations section of the collaborative ISD, where an object added to the annotation section of the collaborative ISD is added as an annotation of the object.

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6. The method of claim 1 , where the content includes code for a scripting language used to present the content at the client device.

7. The method of claim 6 , where the code for the scripting language, upon execution, identifies or describes at least one of the one or more action links.

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8. A service comprising: at least one processor; memory coupled to the at least one processor, and a matching engine implemented at least in part by the at least one processor and via which the service is configured to perform actions comprising: receiving a vocal rendition that originates live from a user; generating a melody representation of the received vocal rendition; selecting, based on the melody representation, at least one candidate based on aligning features of the melody representation with features of the at least one candidate; adding, based on a weighting of the at least one candidate, the selected at least one candidate to a list; and returning the list to the user.

10. The service of claim 8 where the features of the candidate are based on notes of the candidate.

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13. The method of claim 12 , wherein the at least one continuous feature will have a mean and variance for each value of the at least one latent variable.

14. The method of claim 13 , wherein the at least one continuous feature will have a weight for each value of the at least one latent variable.

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11. The system of claim 10 , the operations further comprising: increasing contrast of the high dynamic range image including normalizing pixel values in the high dynamic range image.

12. The system of claim 11 , wherein normalizing pixel values in the high dynamic range image comprises: computing a mean and variance of pixel values in the high dynamic range image; and scaling pixel values in the high dynamic range image according to the computed mean and variance.

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32. The method of claim 31 including the further step of broadcasting events to mobile agent objects associated with the group.

31. The method of claim 30 including the further step of executing the hail function through an agent manager.

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13. A computer-readable program product comprising software stored on a non-transitory computer-readable storage medium, the software comprising: (A) an automatic document processing mechanism that processes the electronic document and automatically produces selective highlighting for at least a portion of the electronic document to enhance the comprehension of the electronic document by a human reader, the automatic document processing mechanism determining which portions of the electronic document to selectively highlight based on user preferences that include a specification of at least one word in the electronic document that triggers highlighting of a corresponding portion of the electronic document, the automatic document processing mechanism including: (A1) a display mechanism that displays the selective highlighting in a display of the electronic document; and (A2) a conversion mechanism that generates a new electronic document that includes all information in the electronic document and additionally includes at least one markup language tag that specifies to the automatic document processing mechanism how to perform at least a portion of the selective highlighting of the new electronic document.

16. The program product of claim 13 further comprising a mechanism for automatically enabling, disabling and adjusting the selective highlighting according to actions of the human reader in browsing the electronic document when the electronic document is displayed.

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7. The device according to claim 1 , wherein the data extractor ( 12 ) selects singular situations, situations having varied, and plausible projected situations.

1. A data-processing device ( 1 ) comprising: a memory ( 10 ) organized into two spaces, a first space containing attributes describing the stored data, and a second space containing connexity links among the stored data, and, according to one or more dimensions respectively associated with the attributes and divided into one or more hierarchized segments, the data being inputted by creating, deleting or modifying the values of the attributes characterizing said segments; an integrator ( 11 ) for integrating one or more incoming information streams, which analyzes said streams to determine the data constituting said streams and to structure said data and the attributes thereof according to the organization of said memory ( 10 ); an inference engine ( 14 ) implementing, in parallel or in series, inference rules ( 141 ) grouped together in libraries ( 15 ), said rules ( 141 ) being programmed to regenerate a sequence including at least one segment of the memory, by creating, deleting or modifying at least one of a datum, an attribute value, and a connexity link during the implementation thereof in the at least one space of the memory, a resources allocator ( 13 ), which activates or deactivates the inference rules ( 141 ) on the basis of a priority rule, a data extractor ( 12 ), which identifies data by programming and by at least one of a selected attribute value and a selected connexity link, located in one or more selected segments of the memory ( 10 ), and providing identified data in one or more outgoing information streams.

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9. A system comprising: a computer processor; computer readable storage medium coupled to the computer processor, the computer readable storage medium including one or more documents containing a first flow diagram in one or more diagram formats supported by the documents; an extractor configured to extract from the first flow diagram one or more flow graphs comprising extracted nodes and edges, and extract from the first flow diagram relational, geometric and textual features for the extracted nodes and edges; a classifier trained to learn rules to recognize process semantics based on the relational, geometric and textual features of the extracted nodes and edges, the rules configured as a decision tree; and generated, based on the learned rules, process modeling recognition code to recognize and decide process semantics in a second flow diagram.

12. The system of claim 9 , wherein the relational features include at least one of the number of incoming extracted edges and the number of outgoing extracted edges associated with an extracted node or edge from the extracted nodes and edges.

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3. A method as recited in claim 1 , wherein the indication comprises an indication that the web page is to be published.

1. A method of including search result based content in a web page, comprising: receiving a search criteria, wherein the search criteria specifies that a search result based content includes content from pages that match a language with which the web page is associated, and wherein the language comprises a primary language associated with the web page; receiving a display format; receiving a life cycle state; receiving an update schedule; receiving an indication that the search result based content is to be included in the web page; generating automatically for the web page a computer script or code configured to enable the search result based content to be retrieved in accordance with the search criteria, display format, life cycle state and update schedule; determining based at least in part on the update schedule to use the computer script or code to perform a search; receiving a set of search results of the search matching the search criteria and the life cycle state; including in the search result based content a content from a page that satisfies the search criteria and is associated with a secondary or default language associated with the web page, in the event a corresponding page associated with the primary language is not found; and using the set of search results to generate for the web page automatically the search result based content to be included in the web page based at least in part on the display format.

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5. The method of claim 1 , wherein the data item is a hyperlink.

1. A method comprising: determining, by use of a networked computer system, that a webpage permits modification; based on the webpage permitting modification, comparing a portion of text contained in the webpage to at least one character string stored in a database, the at least one character string respectively corresponding to at least one data item; based on the portion of text contained in the webpage matching the character string stored in the database, modifying the webpage by inserting the corresponding data item into the webpage, the data item linking the webpage with a different webpage, both the webpage and the different webpage being contained on the same website, the modifying performed by the networked computer system; sending, by the networked computer system, the modified webpage to a web browser of a user; correlating the portion of text contained in the webpage with a common name stored in the database; and communicating, by the networked computer system, the corresponding common name to a producer of the portion of text contained in the webpage.

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2. The method of claim 1 , wherein the generating each of the one or more wrapping regions in the wrapping region collection comprises: identifying, by the processor, a first text fragment from among the one or more text fragments; assigning, by the processor, a current text fragment flag to the first text fragment, the current text fragment flag indicating a single one of the one or more text fragments being processed; generating, by the processor, a current wrapping region and a current fragment run; adding, by the processor, the first text fragment having the current text fragment flag assigned thereto to the current fragment run; identifying, by the processor, a second text fragment from among the one or more text fragments, the second text fragment being horizontally adjacent to the first text fragment having the current text fragment flag assigned thereto, within the predetermined horizontal separation threshold; assigning, by the processor, the current text fragment flag to the second text fragment; adding, by the processor, the second text fragment having the current text fragment flag assigned thereto to the current fragment run; adding, by the processor, the current fragment run to the end of the current wrapping region, wherein the current wrapping region comprises a bounding box comprising borders matching outer borders of fragment runs comprised therein; identifying, by the processor, a third text fragment from among the one or more text fragments, the third text fragment being the leftmost of the one or more text fragments that is within the predetermined vertical separation threshold and the predetermined horizontal separation threshold of a bottom border of the bounding box of the current wrapping region; assigning, by the processor, the current text fragment flag to the third text fragment; removing, by the processor, the contents of the current fragment run; adding, by the processor, the third text fragment having the current text fragment flag assigned thereto to the current fragment run; identifying, by the processor, a fourth text fragment from among the one or more text fragments, the fourth text fragment being horizontally adjacent to the third text fragment having the current text fragment flag assigned thereto, within the predetermined horizontal separation threshold; assigning, by the processor, the current text fragment flag to the fourth text fragment; adding, by the processor, the fourth text fragment having the current text fragment flag assigned thereto to the current fragment run; and adding, by the processor, the current fragment run to the end of the current wrapping region.

3. The method of claim 2 , wherein the identifying the third text fragment is performed in response to identifying the absence of other text fragments from among the one or more text fragments that are horizontally adjacent to the second text fragment.

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17. The method of claim 10 , wherein the method further comprises: in response to receiving a fifth command from the local application to create, update, or delete content based on a name for the content, generating an interest with the content name and a payload that includes a command to create, update, or delete content, wherein the payload further includes authentication information, wherein the interest is transmitted to a remote device and received by a remote component that serves as an interface between a remote application and a portal instance associated with a transport stack of the remote device, and wherein the authentication information is used by the remote component to: authenticate the content producing device; and create, update, or delete the content based on the content name as indicated in the fifth command.

10. A computer-implemented method for facilitating a single interface for file I/O and network communication, the method comprising: receiving, by a content producing device from a local application, a first command to create content, wherein the first command includes a name for the content and access control information that indicates how the content may be accessed, wherein the content name is a hierarchically structured variable length identifier that includes contiguous name components ordered from a most general level to a most specific level; creating a first manifest which is a content object that indicates a set of member content objects by a name and a digest, wherein a name for the first manifest is the content name corresponding to the first command, wherein access to the manifest is based on the access control information included in the first command; and transmitting to the local application the first manifest and an indicator of success for creating the first manifest, thereby facilitating an interface for the local application to process network data in a content centric network; wherein the method is performed by a component that serves as an interface between the local application and a portal instance associated with a transport stack, and wherein the component, the local application, and the transport stack reside on the content producing device.

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1. A computing device comprising: a memory configured to store computer-executable instructions; and a processor in communication with the memory configured to execute the computer-executable instructions to at least: determine, by the computing device, at least a portion of a text string associated with a story; determine, by the computing device, a linguistic element in the text string; analyze, by the computing device, at least one action in the text string by comparing the linguistic element in the text string to a story complexity that comprises an identification of a linear or non-linear story flow; and determine, by the computing device, a maturity level associated with the portion of the text string based on the analysis by at least: determining a violence rating for a particular character in the portion of the text string; and adjusting the maturity level of the portion of the text string to a greater maturity level based in part on the violence rating for the particular character in the portion of the text string.

6. The computing device of claim 1 , wherein analyzing the story complexity further comprises: determining a character in the story; determining a number of other characters that interact with the character; and identifying a greater story complexity when the number of other characters associated with the character exceeds a character threshold.

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8. A non-transitory machine-readable medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 1 .

1. A method, comprising: generating a dictionary comprising (a) one or more transformations of words from singular to plural form and (b) one or more transformations of words from plural to singular form; counting a first number of times that a certain word appears in a set of two or more separate web documents, wherein the certain word is a singular form of the word; counting a second number of times that a transformation of the certain word appears in the set of two or more separate web documents, wherein the transformation of the certain word is a plural form of the certain word; computing a probability by either (a) dividing the second number by the first number or (b) dividing the first number by the second number, removing, from the dictionary, the certain word and the transformation of the certain word in response to determining that the probability is below a particular value; receiving a particular query from a user comprising a plurality of words; based on the particular query, determining whether a particular word in the particular query occurs in the dictionary; selecting from the dictionary a transformation of the particular word; and generating results based on executing a version of the particular query that includes both the particular word and the transformation of the particular word; wherein the method is performed by one or more computing devices.

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11. The system of claim 1 , wherein the at least one object is at least one of a media object, a device object, a location object and a digital document.

1. An annotation system that associates annotations with at least one object, the annotation system comprising: a viewing device for viewing at least one object, the viewing device being separate and distinct from an annotation device; a search circuit that locates the at least one object to be annotated and provides an object identifier that corresponds to the at least one object; the annotation device allowing a user to make at least one annotation independently from the at least one object, the annotation device comprising: an input device that inputs the at least one annotation; an annotation linking circuit that establishes a link, via a processor, associating the at least one annotation with at least one portion of the object; a database that stores the object identifier, the at least one annotation and the link; and a synchronize circuit that associates the at least one annotation with the at least one portion of the object based on the link and the object identifier, wherein the user makes the at least one annotation using the annotation device while viewing the at least one object using the viewing device, and upon synchronization by the synchronize circuit, the at least one annotation is associated with the object identifier at a time different and prior to a time when the synchronize circuit associates the at least one annotation with the at least one portion of the object based on the link and the object identifier, the annotation device stores the at least one annotation in the database, and the viewing device views the at least one annotation from the database.

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8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: selecting, based on a microphone type and a current location of a speaker, a user profile from a plurality of user profiles, wherein the user profile is associated with the speaker; and performing, via a processor, speech recognition on speech received from the speaker using the user profile.

10. The system of claim 8 , wherein each user profile in the plurality of user profiles is associated with the speaker.

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14. The system of claim 1 , wherein the computing system comprises a mechanism for storing and retrieving knowledge to and from the semantic knowledge base that is distributed over multiple computing systems.

1. A system for providing semantic reasoning comprising: an extended semantic model of a specific knowledge domain comprising existing concepts, existing relationships among the existing concepts, and inference logic embedded within each existing concept, wherein each existing concept comprises associated properties and wherein the embedded inference logic is used for inferring values of said associated properties and comprises conditions and processes for drawings inferences about an existing downstream concept that is connected to an existing concept via an existing relationship; a semantic knowledge database being distinct from the extended semantic model and comprising existing nodes and existing links and wherein the existing nodes represent instances of the existing concepts, and the existing links represent instances of the existing relationships among the existing concepts; an inference engine configured to populate the semantic knowledge database with said instances of the existing concepts and said instances of the existing relationships by following the inference logic embedded within each existing concept, and wherein the inference engine adds new nodes and new links to the semantic knowledge database by first receiving external data, next generating instances of fact nodes and associated links representing said external data, and then recursively adding and updating downstream insight nodes and associated links; a computing system comprising at least a processor configured to execute the inference engine operating on the inference logic of the extended semantic model and to host the semantic knowledge database; wherein each existing node comprises existing notes representing instances of the associated properties of each existing concept; wherein the existing links that connect the existing nodes comprise directionality originating from an upstream node and terminating at a downstream node; and wherein the system further comprises a user interface configured to query the semantic knowledge database and to provide decision support to a user.

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13. A computer-implemented method, comprising: receiving information describing a business object type; and in response to user input, creating a definition of the business object type, the definition being in accordance with a data model usable to define business object types, the data model being a standard data model used in an enterprise system, the definition of the business object type including an object key, the creating of the definition of the business object type including creating the object key in accordance with an object key of the data model.

14. The method of claim 13 , the enterprise system comprising a technology stack, the method further comprising: providing an application programming interface that uses the data model to interface with calling applications from the technology stack.

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7. The method of claim 6 , wherein the associated data comprises text data.

6. A computer implemented method for providing an interactive tooltip associated with data in an editing location of an electronic document, the method comprising: providing, by the computer, a first text string displayed in the interactive tooltip in response to a user entering the function name, in proximity to the associated data in the editing location of the electronic document comprising a function name that provides a link to help information corresponding to the associated data in the editing location of the electronic document, wherein the electronic document comprises a spreadsheet and the editing location comprises a data cell of the spreadsheet; and providing a second text string displayed in the interactive tooltip in proximity to the associated data in the editing location of the electronic document comprising an argument name identifying an argument name as being currently entered and describing data required for a function that operates as a selection tool for selecting a portion of the associated data in the editing location of the electronic document.

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27. The article of manufacture of claim 21 , the process further comprising: identifying a non-conforming shape from the one or more non-conforming shapes, wherein the one or more non-conforming shapes do not satisfy a requirement that require respective widths of the one or more non-conforming shapes correspond to widths associated with tracks in recognized or legal track patterns; determining whether or not the non-conforming shape violates a design rule; and determining whether a shape in the region resolves the error.

21. An article of manufacture comprising a non-transitory computer accessible storage medium having stored thereupon a sequence of instructions which, when executed by at least one customizable processor executing one or more threads, causes the at least one customizable processor to perform a set of acts for checking or verifying shapes in an electronic design, the set of acts comprising: using a computer system to execute a process, the process comprising: identifying or determining a dictionary for an electronic design; reducing, at a sliced line module stored at least partially in memory and including or function in conjunction with one or more microprocessors of the computer system, dimensionality of design data in a region at least by identifying or determining a first sliced line for the region in the electronic design, wherein the first sliced line includes one or more projected boundaries of the region; and checking or verifying the electronic design to flag one or more non-conforming shapes by using at least the first sliced line.