| license: cc-by-nc-sa-4.0 | |
| language: | |
| - de | |
| tags: | |
| - embeddings | |
| - clustering | |
| - benchmark | |
| size_categories: | |
| - 10K<n<100K | |
| This dataset can be used as a benchmark for clustering word embeddings for <b>German</b>. | |
| The datasets contains news article titles and is based on the dataset of the [One Million Posts Corpus](https://ofai.github.io/million-post-corpus/) and [10kGNAD](https://github.com/tblock/10kGNAD). It contains 10'275 unique samples, 10 splits with 1'436 to 9'962 samples and 9 unique classes. Splits are built similarly to MTEB's [TwentyNewsgroupsClustering](https://huggingface.co/datasets/mteb/twentynewsgroups-clustering). | |
| 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. | |
| If you use this dataset in your work, please cite the following paper: | |
| ``` | |
| @inproceedings{wehrli-etal-2023-german, | |
| title = "{G}erman Text Embedding Clustering Benchmark", | |
| author = "Wehrli, Silvan and | |
| Arnrich, Bert and | |
| Irrgang, Christopher", | |
| editor = "Georges, Munir and | |
| Herygers, Aaricia and | |
| Friedrich, Annemarie and | |
| Roth, Benjamin", | |
| booktitle = "Proceedings of the 19th Conference on Natural Language Processing (KONVENS 2023)", | |
| month = sep, | |
| year = "2023", | |
| address = "Ingolstadt, Germany", | |
| publisher = "Association for Computational Lingustics", | |
| url = "https://aclanthology.org/2023.konvens-main.20", | |
| pages = "187--201", | |
| } | |
| ``` |