Abstract
In this paper, we propose an efficient collaborative recommendation method for IPTV services. Our method solves the scalability and sparsity problems which the conventional algorithms suffer from in the IPTV environment characterized by the large numbers of users and contents. Our method groups users of similar preferences and utilizes the group profile information for recommending contents in a more specialized manner to the target user. We experimented with our method using the data of the actual one-month IPTV services. The experiment results showed the success rate of 93.58% and the precision of 77.40%, which are recognized as a good performance for IPTV services.
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Kim, MW., Song, WM., Song, SY., Kim, EJ. (2012). Efficient Collaborative Recommendation with Users Clustered for IPTV Services. In: Lee, G., Howard, D., Ślęzak, D., Hong, Y.S. (eds) Convergence and Hybrid Information Technology. ICHIT 2012. Communications in Computer and Information Science, vol 310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32692-9_51
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DOI: https://doi.org/10.1007/978-3-642-32692-9_51
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