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Weighted Markov Model for Recommending Personalized Broadcasting Contents  

Park, Sung-Joon (공주영상대학 모바일게임과)
Hong, Jong-Kyu (충남대학교 컴퓨터공학과)
Kang, Sang-Gil (인하대학교 컴퓨터공학부)
Kim, Young-Kuk (충남대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.12, no.5, 2006 , pp. 326-338 More about this Journal
Abstract
In this paper, we propose the weighted Markov model for recommending the users' prefered contents in the environment with considering the users' transition of their content consumption mind according to the kind of contents providing in time. In general, TV viewers have an intention to consume again the preferred contents consumed in recent by them. In order to take into the consideration, we modify the preference transition matrix by providing weights to the consecutively consumed contents for recommending the users' preferred contents. We applied the proposed model to the recommendation of TV viewer's genre preference. The experimental result shows that our method is more efficient than the typical methods.
Keywords
Broadcasting Contents; Personalization; Recommendation; Markov model;
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