DocumentCode
402849
Title
Dynamic load balancing algorithms for sequence mining
Author
Ma, Chuan-xiang ; Li, Qing-Hua ; Jian, Zhong ; Wang, Huiw
Author_Institution
Sch. of Comput. Sci., Huazhong Univ. of Sci. & Technol., China
Volume
1
fYear
2003
fDate
2-5 Nov. 2003
Firstpage
9
Abstract
Mining sequential patterns in large database is an important problem in data mining research. Enormous sizes of available datasets and possibly large number of mined patterns demand efficient and scalable algorithms. In this paper, we present a new dynamic load algorithm based HPSPM (hash-based parallel algorithm for mining sequential patterns) on shared-nothing environment. Experiments on Dawning 300 cluster system show that this algorithm achieves good speedup and is substantially improved compared to HPSPM.
Keywords
data mining; database management systems; parallel algorithms; resource allocation; workstation clusters; Dawning 300 cluster system; data mining; dynamic load balancing; hash-based parallel algorithm; large database; scalable algorithms; sequence patterns mining; shared-nothing environment; Clustering algorithms; Computer science; Data mining; Databases; Heuristic algorithms; High performance computing; Itemsets; Load management; Parallel algorithms; Partitioning algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/ICMLC.2003.1264432
Filename
1264432
Link To Document