Title
Decomposition-Based Simulated Annealing Technique For Data Clustering
Abstract
It has been demonstrated that simulated annealing provides high-quality results for the data clustering problem. However, existing simulated annealing schemes are memory-based algorithms; they are not suited for solving large problems such as data clustering which typically are too big to fit in the memory space in its entirety. Various buffer replacement policies, assuming either temporal or spatial locality, are not useful in this case since simulated annealing is based on a randomized search process. Poor locality of references will cause the memory to thrash because too many replacements are required.
Publication Date
1-1-1994
Publication Title
Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems
Number of Pages
117-128
Document Type
Article; Proceedings Paper
Identifier
scopus
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0028022225 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0028022225
STARS Citation
Hua, Kien A.; Lang, S. D.; and Lee, Wen K., "Decomposition-Based Simulated Annealing Technique For Data Clustering" (1994). Scopus Export 1990s. 433.
https://stars.library.ucf.edu/scopus1990/433