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An Adaptive Recommendation Service Scheme Using Context-Aware Information in Ubiquitous Environment  

Choi, Jung-Hwan (성균관대학교 휴대폰학과)
Ryu, Sang-Hyun (성균관대학교 전자전기컴퓨터공학과)
Jang, Hyun-Su (성균관대학교 전자전기컴퓨터공학과)
Eom, Young-Ik (성균관대학교 정보통신공학부)
Publication Information
Journal of KIISE:Software and Applications / v.37, no.3, 2010 , pp. 185-193 More about this Journal
Abstract
With the emergence of ubiquitous computing era, various models for providing personalized service have been proposed, and, especially, several recommendation service schemes have been proposed to give tailored services to users proactively. However, the previous recommendation service schemes utilize a wide range of data without and filtering and consider the limited context-aware information to predict user preferences so that they are not adequate to provide personalized service to users. In this paper, we propose an adaptive recommendation service scheme which proactively provides suitable services based on the current context. We use accumulated interaction contexts (IC) between users and devices for predicting the user's preferences and recommend adaptive service based on the current context by utilizing clustering and collaborative filtering. The clustering algorithm improves efficiency of the recommendation service by focusing and analyzing the data that is collected from the locations nearby the users. Collaborative filtering guarantees an accurate recommendation, even when the data is insufficient. Finally, we evaluate the performance and the reliability of the proposed scheme by simulations.
Keywords
Recommender System; Collaborative Filtering; Clustering Algorithm; Context Awareness; Ubiquitous Computing;
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