Topic-sensitive probabilistic model for expert finding in question answer communities

Guangyou Zhou, Siwei Lai, Kang Liu, Jun Zhao
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
In this paper, we address the problem of expert finding in community question answering (CQA). Most of the existing approaches attempt to find experts in CQA by means of link analysis techniques. However, these traditional techniques only consider the link structure while ignore the topical similarity among users (askers and answerers) and user expertise and user reputation. In this study, we propose a topic-sensitive probabilistic model, which is an extension of PageRank algorithm to find
more » ... ts in CQA. Compared to the traditional link analysis techniques, our proposed method is more effective because it finds the experts by taking into account both the link structure and the topical similarity among users. We conduct experiments on real world data set from Yahoo! Answers. Experimental results show that our proposed method significantly outperforms the traditional link analysis techniques and achieves the state-of-the-art performance for expert finding in CQA.
doi:10.1145/2396761.2398493 dblp:conf/cikm/ZhouLLZ12 fatcat:qyy5v2oqo5bedh6u4jiiwanq3i