---
license: cc-by-nc-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 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 18'084 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 [ArxivClusteringP2P](https://huggingface.co/datasets/mteb/arxiv-clustering-p2p).

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",
}
```