Expert finding in question-answering websites: a novel hybrid approach

  • Authors:
  • Wei-Chen Kao;Duen-Ren Liu;Shiu-Wen Wang

  • Affiliations:
  • National Chiao Tung University;National Chiao Tung University;National Chiao Tung University

  • Venue:
  • Proceedings of the 2010 ACM Symposium on Applied Computing
  • Year:
  • 2010

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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, and knowledge sharing through question answering websites is interfered. 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. The experiment results show that our proposed methods outperform other conventional methods.