Integrating expert profile, reputation and link analysis for expert finding in question-answering websites

Duen-Ren Liu*, Yu Hsuan Chen, Wei Chen Kao, Hsiu Wen Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

Abstract

Question answering websites are becoming an ever more popular knowledge sharing platform. On such websites, people may ask any type of question and then wait for someone else to answer the question. However, in this manner, askers may not obtain correct answers from appropriate experts. Recently, various approaches have been proposed to automatically find experts in question answering websites. In this paper, we propose a novel hybrid approach to effectively find experts for the category of the target question in question answering websites. Our approach considers user subject relevance, user reputation and authority of a category in finding experts. A user's subject relevance denotes the relevance of a user's domain knowledge to the target question. A user's reputation is derived from the user's historical question-answering records, while user authority is derived from link analysis. Moreover, our proposed approach has been extended to develop a question dependent approach that considers the relevance of historical questions to the target question in deriving user domain knowledge, reputation and authority. We used a dataset obtained from Yahoo! Answer Taiwan to evaluate our approach. Our experiment results show that our proposed methods outperform other conventional methods.

Original languageEnglish
Pages (from-to)312-329
Number of pages18
JournalInformation Processing and Management
Volume49
Issue number1
DOIs
StatePublished - 1 Jan 2013

Keywords

  • Community
  • Expert finding
  • Link analysis
  • Question answering
  • User reputation
  • Yahoo! Answer Taiwan

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