By Topic

Two-phase Incremental Clustering Algorithm Based on Immune Response and Ant Colony

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

3 Author(s)
Xianghua Li ; Dept. of Comput. Sci. & Technol., Jilin Univ., Zhuhai, China ; Zhengxuan Wang ; Shoukong Chen

It is a trend for paradigms of nature-inspired computing to hybrid. Inspired by the principle of immune response in the immune system, a novel incremental data clustering algorithm called IRA was proposed in previous work. It obtains high quality clustering. However, the number of clusters obtained by IRA is more than the actual ones. Therefore, the clustering algorithm based on ant colony called OAA is taken into account to optimize the results of IRA. Then, both IRA and OAA form a two-phase incremental clustering algorithm. The experimental results are presented and discussed which demonstrate acceptable accuracy couple with efficiency in running time and compression.

Published in:

Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on

Date of Conference:

13-15 Dec. 2010