Citation Author Topic Model in Expert Search
Yuancheng Tu, Nikhil Johri, Dan Roth, Julia Hockenmaier · 2010
This paper proposes a novel topic model, Citation-Author-Topic (CAT) model that addresses a semantic search task we define as expert search – given a research area as a query, it returns names of experts in this area. For example, Michael Collins would be one of the top names retrieved given the query Syntactic Parsing. Our contribution in this paper is two-fold. First, we model the cited author informa-tion together with words and paper au-thors. Such extra contextual information directly models linkage among authors and enhances the author-topic association, thus produces more coherent author-topic distribution. Second, we provide a prelim-inary solution to the task of expert search when the learning repository contains ex-clusively research related documents au-thored by the experts. When compared with a previous proposed model (Johri et al., 2010), the proposed model pro-duces high quality author topic linkage and achieves over 33 % error reduction evaluated by the standard MAP measure-ment. 1