Video Recommendation Using Neuro-Fuzzy on Social TV Environment

  • Duc Anh Nguyen
  • Trong Hai Duong
Conference paper

DOI: 10.1007/978-3-319-17996-4_26

Volume 358 of the book series Advances in Intelligent Systems and Computing (AISC)
Cite this paper as:
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

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.

Keywords

Ontology Smart TV Video Recommendation system and Neural network 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Duc Anh Nguyen
    • 1
  • Trong Hai Duong
    • 1
  1. 1.School of Computer Science and EngineeringInternational University, Vietnam National University HCMCHo Chi MinhVietnam