1 / 16

A PDD Approach for Expert Finding

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.

debbie
Download Presentation

A PDD Approach for Expert Finding

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A PDD Approach for Expert Finding Fu Yupeng Tsinghua Univ

  2. Backgroud • Finding a expert in an organization using corporate information • Frequently asked question • Not well addressed in research • Hot research topic in recent years

  3. 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

  4. 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

  5. Resource distribution

  6. Results

  7. Expertise search model • How deal with topic and expert via documents? • Query-time generated model • Aggregate model Collection Extract Topics Relative Docs Person Profiles Extract Topics Experts Experts

  8. Construction of PDD • Person Description Document (PDD) Context information Distance weighted functional information Group information

  9. Experiments • Component of PDD Performance with different features used solely as PDD

  10. Experiments • Effect of word pair based ranking model

  11. Experiments • Effect of word pair based ranking model Comparison of wordpair-based ranking model effect on features of PDD

  12. Experiments Comparative best results between PDD-based search model and our contrastive model

  13. THU vs MSRA • Context Window • Features • Title,heading12,bold,anchor text • Title, all heading info • People clustering • Structure-based extraction VS Context Vector

  14. Future Work • Employ other resources, especially Emails • Other applications • Software search • MP3 search

  15. Example

  16. Thanks!

More Related