Finding Experts By Semantic Matching of User Profiles
Thiagarajan, Rajesh; Manjunath, Geetha; Stumptner, Markus
Keyword(s): semantics, similarity matching, ontologies, user profile
Abstract: Extracting interest profiles of users based on their personal documents is one of the key topics of IR research. However, when these extracted profiles are used in expert finding applications, only naive text- matching techniques are used to rank experts for a given requirement. In this paper, we address this gap and describe multiple techniques to match user profiles for better ranking of experts. We propose new metrics for computing semantic similarity of user profiles using spreading activation networks derived from ontologies. Our pilot evaluation shows that matching algorithms based on bipartite graphs over semantic user profiles provide the best results. We show that using these techniques, we can find an expert more accurately than other approaches, in particular within the top ranked results. In applications where a group of candidate users need to be short-listed (say, for a job interview), we get very good precision and recall as well.
Additional Publication Information: To be presented at PICKME 2008, a ISWC Workshop, Karlruhe, Germany, to be published in CEUR Workshop proceedings in Oct 2009
External Posting Date: October 21, 2008 [Fulltext]. Approved for External Publication
Internal Posting Date: October 21, 2008 [Fulltext]