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FARS: Fuzzy Ant based Recommender System for Web Users

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

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    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.

    Item Type: Article
    Uncontrolled Keywords: Web personalization, recommender sytems, ant colony optimization, fuzzy set
    Themes: Memory, Text and Place
    Schools: Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
    Journal or Publication Title: International Journal of Computer Science Issues
    Publisher: IJCSI
    Refereed: Yes
    ISSN: 1694-081
    Depositing User: Dr Mo Saraee
    Date Deposited: 26 Oct 2011 15:13
    Last Modified: 20 Sep 2013 16:19
    URI: http://usir.salford.ac.uk/id/eprint/18675

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