DocumentCode
2209107
Title
A parallel tabu search heuristic for clustering data sets
Author
Ng, Michael
Author_Institution
Dept. of Math., Hong Kong Univ., China
fYear
2003
fDate
6-9 Oct. 2003
Firstpage
230
Lastpage
235
Abstract
Clustering methods partition a set of objects into clusters such that objects in the same cluster are more similar to each other than objects in different clusters according to some defined criteria. In this paper, a parallel tabu search heuristic for solving this problem is developed and implemented on a cluster of PCs. We observe that parallelization does not affect the quality of clustering results, but provides a large saving of the computational times in practice.
Keywords
data mining; fuzzy set theory; heuristic programming; optimisation; parallel algorithms; pattern clustering; search problems; workstation clusters; PC clusters; data mining; data set clustering; parallel algorithm; parallel tabu search heuristic; Character generation; Clustering algorithms; Clustering methods; Concurrent computing; Data analysis; Data mining; Fuzzy sets; Mathematics; Personal communication networks; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel Processing Workshops, 2003. Proceedings. 2003 International Conference on
ISSN
1530-2016
Print_ISBN
0-7695-2018-9
Type
conf
DOI
10.1109/ICPPW.2003.1240375
Filename
1240375
Link To Document