Supporting Human Answers for Advice-Seeking Questions in CQA Sites

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• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9626
• 期：1
• 页码：129-141
• 全文大小：245 KB
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• 作者单位：Liora Braunstain (21)
  Oren Kurland (21)
  David Carmel (22)
  Idan Szpektor (22)
  Anna Shtok (21)
  
  21. Faculty of Industrial Engineering and Management, Technion, 32000, Haifa, Israel
  22. Yahoo Labs, 31905, Haifa, Israel
  
• 丛书名：Advances in Information Retrieval
• ISBN：978-3-319-30671-1
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

In many questions in Community Question Answering sites users look for the advice or opinion of other users who might offer diverse perspectives on a topic at hand. The novel task we address is providing supportive evidence for human answers to such questions, which will potentially help the asker in choosing answers that fit her needs. We present a support retrieval model that ranks sentences from Wikipedia by their presumed support for a human answer. The model outperforms a state-of-the-art textual entailment system designed to infer factual claims from texts. An important aspect of the model is the integration of relevance oriented and support oriented features.