FARS: Fuzzy Ant based Recommender System for Web Users

Nadi, S; Saraee, MH; Bagheri, A; Davarpanh Jazi, M

Abstract

Recommender systems are useful tools which provide an
adaptive web environment for web users. Nowadays, having a
user friendly website is a big challenge in e-commerce
technology. In this paper, applying the benefits of both
collaborative and content based filtering techniques is proposed by presenting a fuzzy recommender system based on
collaborative behavior of ants (FARS). FARS works in two
phases: modeling and recommendation. First, user’s behaviors
are modeled offline and the results are used in second phase for online recommendation. Fuzzy techniques provide the possibility of capturing uncertainty among user interests and ant based algorithms provides us with optimal solutions. The performance of FARS is evaluated using log files of “Information and Communication Technology Center” of Isfahan municipality in Iran and compared with ant based recommender system (ARS). The results shown are promising and proved that integrating fuzzy Ant approach provides us with more functional and robust recommendations.

Citation

Nadi, S., Saraee, M., Bagheri, A., & Davarpanh Jazi, M. (2011). FARS: Fuzzy Ant based Recommender System for Web Users. International Journal of Computer Science Issues, 8(1), 203-209

• Journal Article Type: Article
• Publication Date: Jan 1, 2011
• Deposit Date: Oct 26, 2011
• Publicly Available Date: Apr 5, 2016
• Journal: International Journal of Computer Science Issues
• Print ISSN: 1694-0784
• Publisher: IJCSI Press
• Peer Reviewed: Peer Reviewed
• Volume: 8
• Issue: 1
• Pages: 203-209
• Keywords: Web personalization, recommender sytems, ant colony optimization, fuzzy set
• Publisher URL: http://www.ijcsi.org/papers/IJCSI-8-1-203-209.pdf