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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,
idandembedding. Theidcolumns contains the OpenAlex identifier of the record. Theembeddingcolumn 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.
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