| --- |
| dataset_info: |
| features: |
| - name: id |
| dtype: string |
| - name: embedding |
| sequence: float64 |
| splits: |
| - name: train |
| num_bytes: 751739666430 |
| num_examples: 243212198 |
| download_size: 640572858900 |
| dataset_size: 751739666430 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc0-1.0 |
| tags: |
| - openalex |
| - embeddings |
| pretty_name: OpenAlex Mutilingual Embeddings |
| source_dataset: |
| - openalex |
| --- |
| # OpenAlex Multilingual Embeddings |
| This dataset contains multilingual text embeddings of all records in [OpenAlex](https://openalex.org/) with a title or an abstract from the snapshot of 2023-10-20. |
| The dataset was created for the [FORAS project](https://asreview.nl/project/foras/) to investigate the efficacy of |
| different methods of searching in databases of academic publications. All scripts will be available in a [GitHub repository](https://github.com/IDfuse/foras). |
| The project is supported by a grant from the Dutch Research Council (grant no. 406.22.GO.048) |
|
|
| ## Description of the data |
| - The dataset has two columns, `id` and `embedding`. The `id` columns contains the OpenAlex identifier of the record. The `embedding` column contains the text embedding, |
| which is a vector of 384 floats. |
| - The multilingual embedding model [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) was used to generate the embeddings. For every |
| with a title or abstract we generated an embedding of `'query: '` + `title` + `' '` + `abstract`. The model has a maximum token input length of 512 tokens. |
