Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Movie Rating Prediction System of User Propensity Analysis based on Collaborative Filtering and Fuzzy System

협업적 필터링 및 퍼지시스템 기반 사용자 성향분석에 의한 영화평가 예측 시스템

  • 이수진 (부산대학교 전자전기공학과) ;
  • 전태룡 (부산대학교 전자전기공학과) ;
  • 백경동 (부산대학교 전자전기공학과) ;
  • 김성신 (부산대학교 전자전기공학과)
  • Published : 2009.04.25
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Abstract

Recently an intelligent system is developed for the service what users want not a passive system which just answered user's request. This intelligent system is used for personalized recommendation system and representative techniques are content-based and collaborative filtering. In this study, we propose a prediction system which is based on the techniques of recommendation system using a collaborative filtering and a fuzzy system to solve the collaborative filtering problems. In order to verify the prediction system, we used the data that is user's rating about movies. We predicted the user's rating using this data. The accuracy of this prediction system is determined by computing the RMSE(root mean square error) of the system's prediction against the actual rating about the each movie and is compared with the existing system. Thus, this prediction system can be applied to base technology of recommendation system and also recommendation of multimedia such as music and books.

지능형 추천 시스템은 사용자의 요청에 응답하는 수동적인 시스템이 아닌 사용자가 원하는 서비스를 제안하는 시스템으로서 최근 콘텐츠 서비스 분야에 많이 개발되고 있다. 이러한 지능형 추천 시스템은 콘텐츠 개인화 서비스에 응용되고 있으며 대표적인 추천기법으로 내용기반과 협업적 필터링 기법이 있다. 본 연구에서는 협업적 필터링 및 퍼지 시스템을 이용하여 추천 시스템의 기반 기술인 예측 시스템을 제안하였다. 제안한 예측 시스템은 사용자의 과거 영화평가 정보를 바탕으로 영화에 대한 평가점수를 예측한다. 영화평가 예측시스템의 성능은 영화 평가점수의 실제값과 예측값의 오차를 RMSE(root mean square error) 방법으로 계산한 후 기존의 영화평가 시스템 RMSE 값과 비교하여 평가하였다. 본 연구를 통해 제안한 영화평가 예측시스템이 추천 시스템의 기반 기술로서 활용이 가능하고 다른 멀티미디어 컨텐츠 서비스 추천에도 응용이 가능할 것으로 기대한다.

Keywords

References

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