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Proceedings of the First International Conference on Intelligent Human Computer Interaction pp 176–183Cite as

Vote Stuffing Control in IPTV-based Recommender Systems

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Abstract

Vote stuffing is a general problem in the functioning of the content rating-based recommender systems. Currently IPTV viewers browse various contents based on the program ratings. In this paper, we propose a fuzzy clustering-based approach to remove the effects of vote stuffing and consider only the genuine ratings for the programs over multiple genres. The approach requires only one authentic rating, which is generally available from recommendation system administrators or program broadcasters. The entire process is automated using fuzzy c-means clustering. Computational experiments performed over one real-world program rating database shows that the proposed approach is very efficient for controlling vote stuffing.

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Author information

Authors and Affiliations

  1. Samsung India Software R&D Center, Logix Infotech Park, D-5, Sector-59, Noida, 201301, India

    Rajen Bhatt

Authors
  1. Rajen Bhatt
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Editors and Affiliations

  1. Indian Institute of Information Technology, Allahabad, India

    U. S. Tiwary (Professor), Tanveer J. Siddiqui (Assistant Professor), M. Radhakrishna (Professor) & M. D. Tiwari (Director) (Professor),  (Assistant Professor),  (Professor) &  (Director)

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© 2009 Indian Institute of Information Technology, India

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Bhatt, R. (2009). Vote Stuffing Control in IPTV-based Recommender Systems. In: Tiwary, U.S., Siddiqui, T.J., Radhakrishna, M., Tiwari, M.D. (eds) Proceedings of the First International Conference on Intelligent Human Computer Interaction. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-203-1_16

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  • DOI: https://doi.org/10.1007/978-81-8489-203-1_16

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-8489-404-2

  • Online ISBN: 978-81-8489-203-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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