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

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. © 2014 Springer International Publishing.