Mining wikipedia and yahoo! answers for question expansion in opinion QA

  • Authors:

  • Yajie Miao;Chunping Li

  • Affiliations:

  • Tsinghua National Laboratory for Information Science and Technology (TNList), School of Software, Tsinghua University, Beijing, China;Tsinghua National Laboratory for Information Science and Technology (TNList), School of Software, Tsinghua University, Beijing, China

  • Venue:
  • PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
  • Year:
  • 2010

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Abstract

Opinion Question Answering (Opinion QA) is still a relatively new area in QA research. The achieved methods focus on combining sentiment analysis with the traditional Question Answering methods. Few attempts have been made to expand opinion questions with external background information. In this paper, we introduce the broad-mining and deep-mining strategies. Based on these two strategies, we propose four methods to exploit Wikipedia and Yahoo! Answers for enriching representation of questions in Opinion QA. The experimental results show that the proposed expansion methods perform effectively for improving existing Opinion QA models.