title: Expertise finding in bibliographic network: topic dominance learning approach.
abstract: Expert finding problem in bibliographic networks has received increased interest in recent years. This problem concerns finding relevant researchers for a given topic. Motivated by the observation that rarely do all coauthors contribute to a paper equally, in this paper, we propose two discriminative methods for realizing leading authors contributing in a scientific publication. Specifically, we cast the problem of expert finding in a bibliographic network to find leading experts in a research group, which is easier to solve. We recognize three feature groups that can discriminate relevant experts from other authors of a document. Experimental results on a real dataset, and a synthetic one that is gathered from a Microsoft academic search engine, show that the proposed model significantly improves the performance of expert finding in terms of all common information retrieval evaluation metrics.
authors: Mahmood
authors: M
authors: Neshati
authors: Seyyed Hadi
authors: SH
authors: Hashemi
authors: Hamid
authors: H
authors: Beigy