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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Digital TV Program Recommendation System Based on Collaboration Filtering
verfasst von : Fulian Yin, Jianping Chai, Hanlei Wang, Ya Gao
Erschienen in: Bio-Inspired Computing - Theories and Applications
Verlag: Springer Berlin Heidelberg
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In order to solve the problem of information overload brought by over abundant digital television (TV) program resources, this paper proposed a digital TV program recommendation system based on collaborative filtering (CF) which contains information inputting unit, system analysis unit and recommendation sending unit. The audience behavior analysis proposed in this paper was based on two forms: personalized audience behaviour analysis and group audience behaviour analysis, which can recommend interesting TV programs suited for the particular individual or group. The result of simulation proves the feasibility of algorithms.