By Topic

The Research on the Application of Ant Colony Algorithm at Behavior Clustering of Network Users

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

4 Author(s)
Song Bin ; Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China ; Wang Ping-Li ; Wang Ling ; Zhao Yang

It is obvious that internet has become a key media to share resources and exchange information. As a special category of social activities, the behavior from network users normally shows its complexity and diversity, which makes people pay an increased attention to study and manage it. Based upon the formation mechanism of ant colony, this paper proposes an ant colony algorithm to do cluster analysis of network user behavior. The advantages of this algorithm include: zero user interference; no predefined cluster numbers; arbitrary-shaped cluster recognition; no requirement for date types; outlier points insensitivity and so on. Our experimental analysis shows the effectiveness of this algorithm.

Published in:

Internet Technology and Applications, 2010 International Conference on

Date of Conference:

20-22 Aug. 2010