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Application of Research Paper Recommender System to Digital Library

연구논문 추천시스템의 전자도서관 적용방안

  • Received : 2010.10.14
  • Accepted : 2010.11.25
  • Published : 2010.11.28

Abstract

The progress of computers and Web has given rise to a rapid increase of the quantity of the useful information, which is making the demand of recommender systems widely expanding. Like in other domains, a recommender system in a digital library is important, but there are only a few studies about the recommender system of research papers, Moreover none is there in korea to our knowledge. In the paper, we seek for a way to develop the NDSL recommender system of research papers based on the survey of related studies. We conclude that NDSL needs to modify the way to collect user's interests from explicit to implicit method, and to use user-based and memory-based collaborative filtering mixed with contents-based filtering(CF). We also suggest the method to mix two filterings and the use of personal ontology to improve user satisfaction.

컴퓨터와 웹의 발달은 사람들이 이용할 수 있는 정보의 양을 급격히 늘렸으며, 이로 인해 추천시스템에 대한 수요가 증가하고 있다. 전자도서관에서도 다른 분야와 마찬가지로 개인화 및 추천시스템에 대한 연구가 중요한데, 연구논문 추천시스템에 대한 연구는 극히 제한적으로 이뤄지고 있고, 국내에서는 거의 찾아보기 어려울 정도이다. 본 논문에서는 국내외에서 수행된 추천시스템에 대한 연구를 조사분석하고, 이를 토대로 전자도서관 연구논문 추천시스템 구축방안을 KISTI NDSL을 중심으로 제안한다. 현재 NDSL에서 제공하는 알리미서비스를 암묵적 방식으로 바꾸어서 이용자의 프로파일을 구축할 것과 이용자 및 메모리 기반의 협업 필터링을 병행하여 내용기반의 필터링이 가지는 연구논문 추천에서 신규성이 부족한 단점을 보완할 것을 제안한다. 또한 두 기법을 함께 사용하는 방식과 온톨로지와 분할방식에 의한 필터링을 이용하여 추천 만족도를 높이는 방식에 대해서도 제안한다.

Keywords

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