International Journal of Fuzzy Logic and Intelligent Systems

  • 제6권2호
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  • Pages.110-115
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  • 2006
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  • 1598-2645(pISSN)
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  • 2093-744X(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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Collaborative filtering based Context Information for Real-time Recommendation Service in Ubiquitous Computing

  • Lee Se-ll (Dept. of Computer Engineering, Kongju National University) ;
  • Lee Sang-Yong (Division of Computer Science & Engineering, Kongju National University)
  • 발행 : 2006.06.01
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초록

In pure P2P environment, it is possible to provide service by using a little real-time information without using accumulated information. But in case of using only a little information that was locally collected, quality of recommendation service can be fallen-off. Therefore, it is necessary to study a method to improve qualify of recommendation service by using users' context information. But because a great volume of users' context information can be recognized in a moment, there can be a scalability problem and there are limitations in supporting differentiated services according to fields and items. In this paper, we solved the scalability problem by clustering context information per each service field and classifying it per each user, using SOM. In addition, we could recommend proper services for users by quantifying the context information of the users belonging to the similar classification to the service requester among classified data and then using collaborative filtering.

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참고문헌

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