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Preference Difference Metric을 이용한 아이템 분류방식의 추천알고리즘

Recommendation Algorithm by Item Classification Using Preference Difference Metric

  • 박찬수 (중앙대학교 컴퓨터공학과) ;
  • 황태규 (중앙대학교 컴퓨터공학과) ;
  • 홍정화 (중앙대학교 컴퓨터공학과) ;
  • 김성권 (중앙대학교 컴퓨터공학과)
  • 투고 : 2014.09.05
  • 심사 : 2014.12.04
  • 발행 : 2015.02.15

초록

기존의 협업필터링 기반의 추천시스템에 대한 연구는 정확한 평점예측에 집중되면서 추천시스템의 수행시간이 길어지게 되고, 선호아이템을 짧은 시간에 추천해주는 본래의 목적에서 멀어지게 되었다. 본 논문에서는 Preference Difference Metric을 이용하여 평점예측이 아닌 선호 아이템의 분류를 통한 추천을 수행하여 수행시간을 단축하고 정확도를 유지하는 추천 알고리즘을 제안한다.

In recent years, research on collaborative filtering-based recommendation systems emphasized the accuracy of rating predictions, and this has led to an increase in computation time. As a result, such systems have divergeded from the original purpose of making quick recommendations. In this paper, we propose a recommendation algorithm that uses a Preference Difference Metric to reduce the computation time and to maintain adequate performance. The system recommends items according to their preference classification.

키워드

과제정보

연구 과제 주관 기관 : 한국연구재단

참고문헌

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