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Advanced Computational Methods for Knowledge Engineering pp 291–298Cite as

Video Recommendation Using Neuro-Fuzzy on Social TV Environment

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 358))

Abstract

Prior collaborative filtering (CF) methods based on neighbors’ ratings to predict a target user’s rating. In this work, we consider recommendation on the context of Social TV (STV). The watchers/users may either share, comment, rate, or tag videos they are interested in. Each video must be watched and rated by many users. For these assumptions, we proposed a novel model-based collaborative filtering using a fuzzy neural network to learn user’s social web behaviors for video recommendation on STV. We use netflix data-set to evaluate the proposed method. The result shown that the proposed approach is a significant effective method.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, International University, Vietnam National University HCMC, Ho Chi Minh, Vietnam

    Duc Anh Nguyen & Trong Hai Duong

Authors
  1. Duc Anh Nguyen
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  2. Trong Hai Duong
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Editor information

Editors and Affiliations

  1. LITA - UFR MIM, University of Lorraine – Metz, Metz, France

    Hoai An Le Thi

  2. Institute of Informatics & Wrocław University of Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  3. Department of Networked Systems and Services, Budapest University of Technology and Economics, Budapest, Hungary

    Tien Van Do

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Nguyen, D.A., Duong, T.H. (2015). Video Recommendation Using Neuro-Fuzzy on Social TV Environment. In: Le Thi, H., Nguyen, N., Do, T. (eds) Advanced Computational Methods for Knowledge Engineering. Advances in Intelligent Systems and Computing, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-319-17996-4_26

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  • DOI: https://doi.org/10.1007/978-3-319-17996-4_26

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17995-7

  • Online ISBN: 978-3-319-17996-4

  • eBook Packages: EngineeringEngineering (R0)

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