Volume 4, Issue 4 (12-2012)                   IJICTR 2012, 4(4): 69-77 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Tavakolian R, Taghi Hamidi Beheshti M, Moghaddam Charkari N. An Improved Recommender System Based on Forgetting Mechanism for User Interest-Drifting . IJICTR. 2012; 4 (4) :69-77
URL: http://ijict.itrc.ac.ir/article-1-174-en.html
1- Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran, Iran
Abstract:   (840 Views)

Highly effective recommender systems may still face users’ interest drifting. One of the main strategies for handling interest-drifting is forgetting mechanism. Current approaches based on forgetting mechanism have some drawbacks: (i) Drifting times are not considered to be detected in user interest over time. (ii) They are not adaptive to the evolving nature of user’s interest. Until now, there hasn’t been any study to overcome these problems. This paper discusses the above drawbacks and presents a novel recommender system, named WmIDForg, using web usage mining, web content mining techniques, and forgetting mechanism to address user interest-drift problem. We try to detect evolving and time-variant patterns of users' interest individually, and then dynamically use this information to predict favorite items of the user better over time. The experimental results on EachMovie dataset demonstrate our methodology increases recommendations precision 6.80% and 1.42% in comparison with available approaches with and without interest-drifting respectively.

Full-Text [PDF 1996 kb]   (374 Downloads)    
Type of Study: Research | Subject: IT

Add your comments about this article : Your username or Email:
CAPTCHA code