The Community for Technology Leaders
RSS Icon
Subscribe
Los Angeles, CA
March 31, 2009 to April 2, 2009
ISBN: 978-0-7695-3507-4
pp: 431-435
ABSTRACT
In this paper, reclassification for the current classification through K-means would be implemented based on the feedback of web usage mining in order to improve the accuracy of news recommendation and convergence of classification. It could extract most relative keywords and eliminate the disturbance of multi-vocal word in one category based on feedback of web usage. The reclassification of news contents would be implemented based on K-Means algorithm and web usage mining result. We call this method as ReK-means. By simulation comparing, accuracy of reclassification were obvious to be improved compared with related words classification algorithm.
INDEX TERMS
news recommendation, web mining, machine learning
CITATION
Ping Ni, Jianxin Liao, Xiaomin Zhu, Keyan Ren, "News Contents Recommendation Model Based on Feedback of Web Usage", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 431-435, doi:10.1109/CSIE.2009.104
16 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool