Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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User-oriented Paper Search System by Relative Network

상대네트워크 구축에 의한 맞춤형 논문검색 시스템 모델링

  • 조영임 (수원대학교 IT대학 컴퓨터학과) ;
  • 강상길 (수원대학교 IT대학 컴퓨터학과)
  • Published : 2006.06.01
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Abstract

In this paper we propose a novel personalized paper search system using the relevance among user's queried keywords and user's behaviors on a searched paper list. The proposed system builds user's individual relevance network from analyzing the appearance frequencies of keywords in the searched papers. The relevance network is personalized by providing weights to the appearance frequencies of keywords according to users' behaviors on the searched list, such as 'downloading,' 'opening,' and 'no-action.' In the experimental section, we demonstrate our method using 100 users' search information in the University of Suwon.

이 논문은 사용자의 쿼리와 사용자의 행동양식을 바탕으로 상대네트워크를 구축함으로써 개인화된 논문검색 시스템을 모델링한 것이다. 제안하는 시스템은 사용자가 검색한 논문에서 키워드의 빈도수를 분석하여 개인적 상대네트워크를 구축하게 되는데, 이 네트워크는 다운로드, 열기, 삭제 등과 같은 사용자의 행동으로부터 키워드간 가중치를 조정을 함으로써 구축된다. 시스템의 성능평가를 위해 수원대학교에 있는 100명의 사용자들을 대상으로 실험한 결과, 기존의 검색엔진을 사용했을 때보다 성능이 우수하여 사용자 만족도가 높게 나타남을 알 수 있었다

Keywords

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