metadata

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 with a title or an abstract from the snapshot of 2023-10-20. The dataset was created for the FORAS project to investigate the efficacy of different methods of searching in databases of academic publications. All scripts will be available in a GitHub repository. 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 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.