Understanding and summarizing answers in community-based question answering services

  • Authors:

  • Yuanjie Liu;Shasha Li;Yunbo Cao;Chin-Yew Lin;Dingyi Han;Yong Yu

  • Affiliations:

  • Shanghai Jiao Tong University, Shanghai, China;National University of Defense Technology, Changsha, China;Shanghai Jiao Tong University, Shanghai, China and Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;Shanghai Jiao Tong University, Shanghai, China;Shanghai Jiao Tong University, Shanghai, China

  • Venue:
  • COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
  • Year:
  • 2008

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Abstract

Community-based question answering (cQA) services have accumulated millions of questions and their answers over time. In the process of accumulation, cQA services assume that questions always have unique best answers. However, with an in-depth analysis of questions and answers on cQA services, we find that the assumption cannot be true. According to the analysis, at least 78% of the cQA best answers are reusable when similar questions are asked again, but no more than 48% of them are indeed the unique best answers. We conduct the analysis by proposing taxonomies for cQA questions and answers. To better reuse the cQA content, we also propose applying automatic summarization techniques to summarize answers. Our results show that question-type oriented summarization techniques can improve cQA answer quality significantly.