By Topic

A Collaborative Filtering Recommendation Based on User Profile Weight and Time Weight

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)
Chen Dongtao ; Sch. of Econ. & Manage., Tongji Univ., Shanghai, China ; Xu Dehua

Collaborative Filtering (CF) has proven to be the most widely used recommendation technology. However, the conventional CF ignores the impacts of user similarity caused by user profile, and it also can't reflect the changes of user's interests. To solve this problem, two weights are proposed: the user profile weight and the time weight. Also, the two weights are combined together and applied to a novel personalized recommendation system. The experimental results show that the improved method can obviously increase the recommendation precision.

Published in:

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Date of Conference:

11-13 Dec. 2009