Intent feature discovery using Q&A corpus and web data

  • Authors:

  • Soungwoong Yoon;Adam Jatowt;Katsumi Tanaka

  • Affiliations:

  • Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, Japan;Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, Japan;Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, Japan

  • Venue:
  • Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
  • Year:
  • 2010

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Abstract

User intent in Web search environment is defined as user's information need, and believed to be found by analyzing past data such as queries, click histories and user profiles. However, users may have different intents even in the same queries. In this paper, we attempt to discover the characteristics of intent through finding its features. Our assumption is that if a user expresses the query which clearly points out to certain intent, s/he can reach an intended Web page using that query. We conceptualize this functionality of intent features using intent evolution procedure, called multiple intent model. We collect candidate intent features using Web Q&A corpus analysis, and suggest the automated judgment method using search engine indexes powered by Click Chain Model to demonstrate the adaptability of candidate intent features. Experimental results show that intent features can be extracted efficiently and provide evidences toward intent discovery without human supervision.