Abstract
Multiple users share a common account in Internet Protocol Television (IP-TV) services. Can such shared accounts be identified solely on the basis of logs recorded by set top boxes (STBs)? Once a shared account is identified, can the different users sharing it be identified as well? We suppose different users within a shared account not only have different preferences for TV programs, but also get used to consuming services in different periods (e.g., after dinner or at weekend). We propose an algorithm to decompose users in composite accounts based on mining different preferences over different periods from consumption logs. In our experiments, the proposed algorithm outperforms traditional user-based collaborative filtering method 3-8 times when leveraging the decomposed users for personalized recommendation.
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Wang, Z., Yang, Y., He, L., Gu, J. (2014). User Identification within a Shared Account: Improving IP-TV Recommender Performance. In: Manolopoulos, Y., Trajcevski, G., Kon-Popovska, M. (eds) Advances in Databases and Information Systems. ADBIS 2014. Lecture Notes in Computer Science, vol 8716. Springer, Cham. https://doi.org/10.1007/978-3-319-10933-6_17
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DOI: https://doi.org/10.1007/978-3-319-10933-6_17
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