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