Harnessing Bibliometric Measures for a Scholarly Paper Recommender System
This demo presents BIBLME RecSys which provides reading recommendations according to the selected paper. The novelty of our proposed approach is leverage the interconnection between Information Retrieval and bibliometrics in order to provides personalized recommendations regardless of the research field and regardless of the user's expertise. This system provides users with papers suggestions guided by the papers they are reading and by the references they contain. To do so, we determine the impact, the inner representativeness, of each bibliographical reference according to their occurrences in the paper the user is reading. As a result, we obtain papers that are related to the paper selected by the user according to the influence of references on it.