DocumentCode :
1055047
Title :
An Efficient Cluster Identification Algorithm
Author :
Kusiak, Andrew ; Chow, Wing S.
Author_Institution :
Department of Mechanical and Industrial Engineering, University of Manitoba, Winnipeg, MB, Canada R3T 2N2
Volume :
17
Issue :
4
fYear :
1987
fDate :
7/1/1987 12:00:00 AM
Firstpage :
696
Lastpage :
699
Abstract :
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.
Keywords :
Clustering algorithms; Computational complexity; Control engineering; Flow production systems; Large-scale systems; Matrix decomposition; Medical expert systems; Pattern analysis; Pattern recognition; Systems biology;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/TSMC.1987.289363
Filename :
4075686
Link To Document :
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