By Topic

An Efficient Cluster Identification 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

2 Author(s)
Kusiak, A. ; Department of Mechanical and Industrial Engineering, University of Manitoba, Winnipeg, MB, Canada R3T 2N2 ; Chow, W.S.

Clustering of large-scale binary matrices requires a considerable computational effort. In some cases this effort is lost since the matrix is not decomposable into mutually separable submatrices. A cluster identification algorithm which has relatively low computational time complexity O(2mn) is developed. It allows checking for the existence of clusters and determines the number of mutually separable clusters. A modified cluster identification algorithm for clustering nondiagonally structured matrices is also presented. The two algorithms are illustrated in numerical examples.

Published in:

Systems, Man and Cybernetics, IEEE Transactions on  (Volume:17 ,  Issue: 4 )