Abstract
How to help the IPTV service provider make the program recommendation to their clients is the problem we propose to solve in this paper. Here we offer an adaptive temporal model to identify multiple members under a shared IPTV account. The time intervals are first detected and defined in each account. Then, the preference similarity is calculated among the intervals to extract the members. After that, we evaluate our model on the industrial data sets by a famous IPTV provider. The experimental results show that our proposed model is promising and outperform the state-of-the-art algorithms with low computational complexity and versatility without user feedback. Furthermore, the proposed model has been officially adopted by the IPTV provider and applied in their IPTV systems with excellent user satisfaction in 2013.
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Yang, Y., Hu, Q., He, L., Ni, M., Wang, Z. (2015). Adaptive Temporal Model for IPTV Recommendation. In: Dong, X., Yu, X., Li, J., Sun, Y. (eds) Web-Age Information Management. WAIM 2015. Lecture Notes in Computer Science(), vol 9098. Springer, Cham. https://doi.org/10.1007/978-3-319-21042-1_21
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DOI: https://doi.org/10.1007/978-3-319-21042-1_21
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