A PDD Approach for Expert Finding一个专家发现PDD方法.pptVIP

A PDD Approach for Expert Finding Fu Yupeng Tsinghua Univ Backgroud Finding a expert in an organization using corporate information Frequently asked question Not well addressed in research Hot research topic in recent years Characteristics Build up a relationship between topics and experts via documents Deal with a mixture of types and formats information in corporate Integrate different kinds of expertise data Models for matching variants of person names and name disambiguation Expertise information recognition and extraction QA techniques TREC2005 Expert Finding Task Aim: Given a query about a region, return a expert list on that domain Resource: Full W3C corpus 1092 candidate list, each one with a unique personid 10 training queries and 50 test queries Resource distribution Results Expertise search model How deal with topic and expert via documents？ Query-time generated model Aggregate model Construction of PDD Person Description Document (PDD) Experiments Component of PDD Experiments Effect of word pair based ranking model Experiments Effect of word pair based ranking model Experiments THU vs MSRA Context Window Features Title,heading12,bold,anchor text Title, all heading info People clustering Structure-based extraction VS Context Vector Future Work Employ other resources, especially Emails Other applications Software search MP3 search Example * * Collection Relative Docs Person Profiles Topics Extract Experts Experts Topics Extract Context information Distance weighted functional information Group information Performance with different features used solely as PDD 0.2667 0.2688 0.1748 0.1736 0.1261 0.1290 Anchor text 0.4060 0.4220 0.2835 0.2890 0.2389 0.2476 Heading12 0.1872 0.1915 0.1297 0.1343 0.0906 0.0911 Bold 0.4140 0.4280 0.2996 0.3060 0.2479 0.2620 Title Without wp With wp Without wp With wp Without wp With wp p@10 R-prec MAP Feature Comparison of wordpair-based ranking model effect on features of PDD 0.3700 0.2668 Best resu