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Multi-perspective User Preference Learning in a Chatting Domain

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2009, 14(1), pp.1-8
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

신욱현 1 정윤재 2 맹성현 1 Kyoung-Soo Han 3

1한국과학기술원
2한국정보통신대학교
3SK텔레콤

Accredited

ABSTRACT

Learning user's preference is a key issue in intelligent system such as personalized service. The study on user preference model has adapted simple user preference model, which determines a set of preferred keywords or topic, and weights to each target. In this paper, we recommend multi-perspective user preference model that factors sentiment information in the model. Based on the topicality and sentimental information processed using natural language processing techniques, it learns a user's preference. To handle time-variant nature of user preference, user preference is calculated by session, short-term and long term. User evaluation is used to validate the effect of user preference learning and it shows 86.52%, 86.28%, 87.22% of accuracy for topic interest, keyword interest, and keyword favorableness.

Citation status

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