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README.md
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@@ -13,4 +13,26 @@ This dataset can be used as a benchmark for clustering word embeddings for <b>Ge
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The datasets contains book titles and is based on the dataset from the [GermEval 2019 Shared Task on Hierarchical Classification of Blurbs](https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/germeval-2019-hmc.html). It contains 17'726 unqiue samples, 28 splits with 177 to 16'425 samples and 4 to 93 unique classes. Splits are built similarly to [MTEB](https://github.com/embeddings-benchmark/mteb)'s [ArxivClusteringS2S](https://huggingface.co/datasets/mteb/arxiv-clustering-s2s).
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Have a look at German Text Embedding Clustering Benchmark ([Github](https://github.com/ClimSocAna/tecb-de), [Paper](https://arxiv.org/abs/2401.02709)) for more infos, datasets and evaluation results.
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The datasets contains book titles and is based on the dataset from the [GermEval 2019 Shared Task on Hierarchical Classification of Blurbs](https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/germeval-2019-hmc.html). It contains 17'726 unqiue samples, 28 splits with 177 to 16'425 samples and 4 to 93 unique classes. Splits are built similarly to [MTEB](https://github.com/embeddings-benchmark/mteb)'s [ArxivClusteringS2S](https://huggingface.co/datasets/mteb/arxiv-clustering-s2s).
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Have a look at German Text Embedding Clustering Benchmark ([Github](https://github.com/ClimSocAna/tecb-de), [Paper](https://arxiv.org/abs/2401.02709)) for more infos, datasets and evaluation results.
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If you use this dataset in your work, please cite the following paper:
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```
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@inproceedings{wehrli-etal-2023-german,
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title = "{G}erman Text Embedding Clustering Benchmark",
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author = "Wehrli, Silvan and
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Arnrich, Bert and
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Irrgang, Christopher",
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editor = "Georges, Munir and
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Herygers, Aaricia and
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Friedrich, Annemarie and
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Roth, Benjamin",
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booktitle = "Proceedings of the 19th Conference on Natural Language Processing (KONVENS 2023)",
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month = sep,
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year = "2023",
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address = "Ingolstadt, Germany",
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publisher = "Association for Computational Lingustics",
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url = "https://aclanthology.org/2023.konvens-main.20",
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pages = "187--201",
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}
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```
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