A hybrid recommender system for dynamic web users

Nadi, S; Saraee, MH; Bagheri, A

Abstract

Nowadays, providing tools that eases the interaction of users with websites is a big challenge in e-commerce. Recommender systems are useful tools which adapts the environment of websites compatible with users needs. In this paper, applying a hybrid collaboration and content based technique a model for recommendation system is proposed. Presented model works in two offline and online
phases. In offline step the behavior of users’ models with a combined FCM and ant based clustering algorithm and in online step suitable recommendations extracts for presenting to active user. The model is implemented and tested as a recommender system for personalizing website of Information and Communication Technology Center” of Isfahan municipality in Iran. The results shown are promising and proved that applying more efficient clustering technique for modeling users behavior provide us with more interesting and useful patterns which consequently making the recommender system more functional and robust.

Citation

Nadi, S., Saraee, M., & Bagheri, A. (2011). A hybrid recommender system for dynamic web users. International Journal of Multimedia and Image Processing, 1(1), 3-8

• Journal Article Type: Article
• Publication Date: Mar 1, 2011
• Deposit Date: Oct 26, 2011
• Journal: International Journal Multimedia and Image Processing
• Peer Reviewed: Peer Reviewed
• Volume: 1
• Issue: 1
• Pages: 3-8
• Publisher URL: http://www.infonomics-society.org/IJMIP/A%20Hybrid%20Recommender%20System%20for%20Dynamic%20Web%20Users.pdf