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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1264432
