A PDD-Based searching approach for expert finding in intranet information management

Authors:
Yupeng Fu;Rongjing Xiang;Min Zhang;Yiqun Liu;Shaoping Ma
Affiliations:
State Key Lab of Intelligent Technology and Systems, Tsinghua University, Beijing;State Key Lab of Intelligent Technology and Systems, Tsinghua University, Beijing;State Key Lab of Intelligent Technology and Systems, Tsinghua University, Beijing;State Key Lab of Intelligent Technology and Systems, Tsinghua University, Beijing;State Key Lab of Intelligent Technology and Systems, Tsinghua University, Beijing
Venue:
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
Year:
2006

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Abstract

Expert finding is a frequently faced problem in Intranet information management, which aims at locating certain employees in large organizations. A Person Description Document (PDD)-based retrieval model is proposed in this paper for effective expert finding. At first, features and context about an expert are extracted to form a profile which is called the expert’s PDD. A retrieval strategy based on BM2500 algorithm and bi-gram weighting is then used to rank experts which are represented by their PDDs. This model proves effective and the method based on this model achieved the best performance in TREC2005 expert finding task.Comparative studies with traditional non-PDD methods indicate that the proposed model improves the system performance by over 45%.