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P-FCloHUS: A Parallel Approach for Mining Frequent Closed High-Utility Sequences on Multi-core Processors
被引:0
|作者:
Hong-Phat Nguyen
[1
,2
]
Bac Le
[1
,2
]
机构:
[1] Univ Sci, Fac Informat Technol, Ho Chi Minh City, Vietnam
[2] Vietnam Natl Univ, Ho Chi Minh City, Vietnam
来源:
关键词:
Data mining;
High-utility sequential pattern mining;
Frequent closed sequence mining;
Multi-core processors;
Parallel mining;
D O I:
10.1007/978-981-19-8234-7_31
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
Frequent closed high-utility (FCHU) sequences are preferable to frequent closed sequences. Not only because of their utility-based nature that considerately contributes to taking decisive business actions, FCHU sequences also preserve necessary information for re-constructing frequent high-utility sequences. Despite of their vital role, mining FCHU sequences is a time consuming task when facing with large-scale datasets, or especially when the input thresholds are relatively small. To contend with these difficulties, this paper proposes a parallel algorithm named P-FCloHUS for fast mining FCHU sequences by making good use of multi-core processors. By relying on a novel Single scan synchronization strategy that is facilitated by an efficiently Partitioned result space structure, P-FCloHUS successfully alleviates the communication cost between mining tasks and hence speeds up the parallel mining process. Experiments on both dense and sparse datasets show that P-FCloHUS outperforms the state-of-the-art FMaxCloHUSM in terms of runtime performance.
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页码:396 / 408
页数:13
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