Paper Info
Title
Tree partition based parallel frequent pattern mining on shared memory systems
Abstract
In this paper, we present a tree-partition algorithm for parallel mining of frequent patterns. Our work is based on FP-Growth algorithm, which is constituted of tree-building stage and mining stage. The main idea is to build only one FP-Tree in the memory, partition it into several independent parts and distribute them to different threads. A heuristic algorithm is devised to balance the workload. Our algorithm can not only alleviate the impact of locks during the tree-building stage, but also avoid the overhead that do great harm to the mining stage. We present the experiments on different kinds of datasets and compare the results with other parallel approaches. The results suggest that our approach has great advantage in efficiency, especially on certain kinds of datasets. As the number of processors increases, our parallel algorithm shows good scalability.
Year
DOI
Venue
2006
10.1109/IPDPS.2006.1639620
IPDPS
Keywords
Field
DocType
fp-growth algorithm,parallel algorithm,parallel mining,mining stage,different thread,parallel approach,shared memory system,tree-building stage,tree partition,tree-partition algorithm,parallel frequent pattern mining,different kind,heuristic algorithm,algorithm design and analysis,pattern recognition,data mining,scalability,computer science,parallel algorithms,association rules
Data mining,Shared memory,Heuristic (computer science),Parallel algorithm,Computer science,Workload,Parallel computing,Thread (computing),FSA-Red Algorithm,Partition (number theory),Scalability
Conference
ISBN
Citations 
PageRank 
1-4244-0054-6
11
0.65
References 
Authors
8
6
Name
Order
Citations
PageRank
Dehao Chen11216.30
chunrong lai2283.83
Wei Hu318214.17
Wenguang Chen4101470.57
Yimin Zhang51536130.17
Weimin Zheng61889182.48