Cart (Loading....) | Create Account
Close category search window
 

Finding item neighbors in item-based collaborative filtering by adding item content

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Tiraweerakhajohn, C. ; Dept. of Comput. Eng., King Mongkut''s Inst. of Technol. Ladkrabang, Bangkok, Thailand ; Pinngern, O.

In this paper we present an approach that tries to alleviate the main item-based collaborative filtering (CF) drawback - the sparsity and the first-rater problem. The contents of items are combined into the item-based CF to find similar items and combined similarity is used to generate predictions. The first step concentrates in using association rules mining methods to discover new similarity relationships among attributes. The second step is to exploit this similarity during the calculation of similar item. Finally, new similarity and rating similarity measures are combined to find neighbor item in item-based CF algorithm and generating ratings predictions based on a combined similarity measure. The experiments show that this novel approach can achieve better prediction accuracy than traditional item-based CF algorithm.

Published in:

Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th  (Volume:3 )

Date of Conference:

6-9 Dec. 2004

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.