By Topic

Research on Personalized Service System in E-Supermarket by using Adaptive Recommendation Algorithm

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

5 Author(s)
Yan-Wen Wu ; Dept. of Inf. & Technol., Central China Normal Univ., Wuhan ; Qi Luo ; Min Liu ; Zheng-Hong Wu
more authors

To meet the personalized needs of customers in e-supermarket, an adaptive recommendation algorithm based on support vector machine was proposed in the paper. First, the commodities that user needed were classified as several categories through support vector machine, which ensured the recall of commodity recommendation. Then vector space model was used for content-based recommendation, specific commodities in several categories were obtained to ensure the precision. The algorithm had two advantages; the first was that it dealt with complex high dimensional data better, which obtained parameters directly form adaptive learning classifier. The second was that it had a better capability of classification. The algorithm was also used in personalized recommendation service system based on e-supermarket. The system could support e-commence better. The results manifested that the algorithm was effective

Published in:

Machine Learning and Cybernetics, 2006 International Conference on

Date of Conference:

13-16 Aug. 2006