Title :
A parallel tabu search heuristic for clustering data sets
Author_Institution :
Dept. of Math., Hong Kong Univ., China
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;
Conference_Titel :
Parallel Processing Workshops, 2003. Proceedings. 2003 International Conference on
Print_ISBN :
0-7695-2018-9
DOI :
10.1109/ICPPW.2003.1240375
