Title : ( Fuzzy-Bayesian Network Approach to Genre-based Recommender Systems )
Authors: Soheila Ashkezari Toussi , Mohammad Reza Akbarzadeh Totonchi ,
Full TextAbstract
The World Wide Web has created a new media for mass marketing that can also be highly customized to online customers’ needs and expectations. Recommender Systems (RS) play an important role in this area. Here, we aim to establish a genre-based collaborative RS to automatically suggest and rank a list of appropriate items (movies) to a user based on the user profile and the past voting patterns of other users with similar tastes. The contribution of this paper is using genre based information in a hybrid fuzzy-Bayesian network collaborative RS. The interest to the different genres is computed based on a hybrid user model. The similarity of likeminded users according to the fuzzy distance and also Pearson correlation coefficient is involved in a Bayesian network.
Keywords
, Fuzzy Bayesian Networks, Recommeder Systems
@inproceedings{paperid:1016293,
author = {Ashkezari Toussi, Soheila and Akbarzadeh Totonchi, Mohammad Reza},
title = {Fuzzy-Bayesian Network Approach to Genre-based Recommender Systems},
booktitle = {2010 World Congress on Computational Intelligence},
year = {2010},
location = {Barcelona},
keywords = {Fuzzy Bayesian Networks; Recommeder Systems},
}
%0 Conference Proceedings
%T Fuzzy-Bayesian Network Approach to Genre-based Recommender Systems
%A Ashkezari Toussi, Soheila
%A Akbarzadeh Totonchi, Mohammad Reza
%J 2010 World Congress on Computational Intelligence
%D 2010
