A Context-Aware Intelligent Recommender System in Ubiquitous Environment

J. Yu and M. Jeon (Korea)


Context-aware applications, AntMiner classification, userprofile learning, recommender system, ubiquitous computing.


With the promotion of ubiquitous computing environment, it has become important for recommender systems to take advantage of contextual information to provide preferable items to a user. According to the current user-centric context, such as a user’s degree of stress, changes in ubiquitous environment, the user preference of items also changes. However, traditional recommender systems just offer preferable items based on the history of user’s service patterns and user preference profile. In this paper, we propose a context-aware intelligent recommender system to provide preferable media service and contents to a user using the user-centric contexts such as 5W1H (Who, When, Where, Why, What, How). The proposed recommender is composed of two detailed components. One is the media service recommender using the history of user’s service patterns and current user-centric contexts. The other is the media contents recommender which is based on the content-based information filtering using contextual information. This paper shows the efficiency of the media service recommender with AntMiner classifier and the media contents recommender with the content-based information filtering approach.

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