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Extending the Bayesian Classifier to a Context-Aware Recommender System for Mobile Devices

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3 Author(s)
Toon De Pessemier ; Dept. of Inf. Technol. (INTEC), IBBT Ghent Univ. Ghent, Ghent, Belgium ; Tom Deryckere ; Luc Martens

Mobile devices that are capable of playing Internet videos have become wide-spread in recent years. Because of the enormous offer of video content, the lack of sufficient presentation space on the screen, and the laborious navigation on mobile devices, the video consumption process becomes more complicated for the end-user. To handle this problem, people need new instruments to assist with the hunting, filtering and selection process. We developed a methodology for mobile devices that makes the huge content sources more manageable by creating a user profile and personalizing the offer. This paper reports the structure of the user profile, the user interaction mechanism, and the recommendation algorithm, an improved version of the Bayesian classifier that incorporates aspects of the consumption context (like time, location, and mood of the user) to make the suggestions more accurate.

Published in:

Internet and Web Applications and Services (ICIW), 2010 Fifth International Conference on

Date of Conference:

9-15 May 2010