A hybrid recommender system based on AHP that awares contexts with Bayesian networks for smart TV

Ji Chun Quan, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Recently, many researchers are paying close attention to TV program recommendation methods because of the enormous increase of available TV programs for users. As TV programs are often watched by multiple users like a family, this paper proposes a smart TV program recommendation method for multi-users using Bayesian networks and AHP (analytic hierarchy process). The proposed method uses Bayesian networks to infer each user's genre preference as well as program preference, and uses AHP to predict group genre preference and choose recommended programs. The accuracy of the Bayesian network model is improved through parameter learning from users' watching history. Experiments verify the inference accuracy of the Bayesian network and the accuracy of programs recommended by the proposed method.

Original languageEnglish
Title of host publicationHybrid Artificial Intelligence Systems - 9th International Conference, HAIS 2014, Proceedings
PublisherSpringer Verlag
Pages527-536
Number of pages10
ISBN (Print)9783319076164
DOIs
Publication statusPublished - 2014 Jan 1
Event9th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2014 - Salamanca, Spain
Duration: 2014 Jun 112014 Jun 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8480 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2014
CountrySpain
CitySalamanca
Period14/6/1114/6/13

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Quan, J. C., & Cho, S. B. (2014). A hybrid recommender system based on AHP that awares contexts with Bayesian networks for smart TV. In Hybrid Artificial Intelligence Systems - 9th International Conference, HAIS 2014, Proceedings (pp. 527-536). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8480 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-07617-1_46