BIBLME RecSys: Harnessing Bibliometric Measures for a Scholarly Paper Recommender System

Anaïs Ollagnier (1) , Sébastien Fournier (2, 1, 3) , Patrice Bellot (1, 4, 5)

1 LIS - Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon)
2 CENS - Centre d'Edition Numérique Scientifique
3 DIMAG - Data, Information & content MAnagement Group
4 CLEO - Centre pour l'édition électronique ouverte
5 AMU - Aix Marseille Université

The iterative continuum of scientific production generates a need for filtering and specific crossing of ideas and papers. In this paper, we present BIBLME RecSys software which is dedicated to the analysis of bibliographical references extracted from scientific collections of papers. Our goal is to provide users with paper suggestions guided by the papers they are reading and by the references they contain. To do so, we propose a new approach based on a new bibliometric measure. We propose to determine the impact, the inner representativeness, of each bibliographical reference according to their occurrences in the paper the user is reading. By means of this approach, we suggest central references of the author's paper. As a result, we obtain papers that are related to the paper selected by the user according to the influence of references on it. We evaluate the recommendation in the context of a digital library dedicated to humanities and social sciences.

Mots clés: Bib- liographic information; Bibliometrics; Digital libraries; Recommender systems; Text mining

Domaines: Informatique [cs]

Anaïs Ollagnier, Sébastien Fournier, Patrice Bellot. BIBLME RecSys: Harnessing Bibliometric Measures for a Scholarly Paper Recommender System. BIR 2018 Workshop on Bibliometric-enhanced Information Retrieval, Mar 2018, Grenoble, France. ⟨hal-01770588⟩