Using Elasticsearch for entity recognition in affiliation disambiguation

Anne L'Hôte (1) , Eric Jeangirard (1)

1 M.E.N.E.S.R. - Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche

Automatic recognition of affiliations in the metadata of scholarly publications is a key point for monitoring and analyzing trends in scientific production, especially in an open science context. We propose an automatic alignment method on registries, based on Elasticsearch. The proposed method is modular and leaves the choice of the alignment criteria to the user, allowing him to keep control over the precision and recall of the method. An implementation is proposed for an automatic alignment on three registries: countries, GRID.ac and RNSR (research laboratory directory in France) on the Github https://github.com/dataesr/matcher and the performances are analyzed in this paper.

Mots clés: Elasticsearch; affiliation disambiguation; entity recognition; open science

Domaines: Bibliothèque électronique [cs.DL]

Anne L'Hôte, Eric Jeangirard. Using Elasticsearch for entity recognition in affiliation disambiguation. 2021. ⟨hal-03365806⟩