A Model to Infer Users' Behavior Patterns for Personalized Recommendation Service based Context-Awareness

컨텍스트 인식 기반 개인화 추천 서비스를 위한 사용자 행동패턴 추론 모델

  • 서효석 (공주대학교 컴퓨터공학과) ;
  • 이상용 (공주대학교 컴퓨터공학부)
  • Received : 2012.03.09
  • Accepted : 2012.03.26
  • Published : 2012.03.31


In order to provide with personalized recommendation service in context-awareness environment, the collected context data should be analyzed fast and the objective of user should be able to inferred effectively. But, the context collected from the mobile devices is not suitable for applying the existing inference algorithms as they are due to the omission or uncertainty of information and the efficient algorithms are required for mobile environment. In this paper, the behavior pattern was classified using naive bayes classification for minimize the loss caused by the omission or error of information. And pattern matching was used to effectively learn of the users inclination and infer the behavior purpose. The accuracy of the suggested inference model was evaluated by applying to the application recommendation service in the smart phones.


Naive Bayes;Pattern matching;Context-awareness;Personalization;Inference