CCSpan: Mining closed contiguous sequential patterns

doi:10.1016/j.knosys.2015.06.014

CORC > 上海财经大学 > 上海财经大学

	CCSpan: Mining closed contiguous sequential patterns
	Zhang, Jingsong 1; Wang, Yinglin 2; Yang, Dingyu 1
刊名	KNOWLEDGE-BASED SYSTEMS
	2015-11
卷号	89 页码:1-13
关键词	Data mining Sequential pattern mining Closed sequential pattern Contiguous constraint Closed contiguous sequential pattern
ISSN号	0950-7051
DOI	10.1016/j.knosys.2015.06.014
英文摘要	Existing closed sequential pattern mining generates a more compact yet complete resulting set compared with general sequential pattern mining. However, conventional closed sequential pattern mining algorithms pose a great challenge at spawning a large number of inefficient and redundant patterns, especially when using low support thresholds or pattern-enriched databases. Driven by wide applications of sequential patterns with contiguous constraint, we propose CCSpan (Closed Contiguous Sequential pattern mining), an efficient algorithm for mining closed contiguous sequential patterns, which contributes to a much more compact pattern set but with the same information w.r.t. closed sequential patterns. Moreover, with the shorter feature of patterns, the closed contiguous sequential patterns are preferred for feature selection and sequence classification based on the Minimum Description Length principle. CCSpan adopts a novel snippet-growth paradigm to generate a series of snippets as candidates, each of which is attached with a set of item(s) that precisely record the pattern's occurrences in the database, and CCSpan leverages three pruning techniques to improve the computational efficiency significantly. Our experiments based on both sparse and dense datasets demonstrated that CCSpan is efficient and scalable in terms of both database size and support threshold. (C) 2015 Elsevier B.V. All rights reserved.
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000364249800001
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/1447]
专题	上海财经大学
通讯作者	Wang, Yinglin
作者单位	1.Shanghai Jiao Tong Univ, Dept CSE, Shanghai 200030, Peoples R China; 2.Shanghai Univ Finance & Econ, Dept CST, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Jingsong,Wang, Yinglin,Yang, Dingyu. CCSpan: Mining closed contiguous sequential patterns[J]. KNOWLEDGE-BASED SYSTEMS,2015,89:1-13.
APA	Zhang, Jingsong,Wang, Yinglin,&Yang, Dingyu.(2015).CCSpan: Mining closed contiguous sequential patterns.KNOWLEDGE-BASED SYSTEMS,89,1-13.
MLA	Zhang, Jingsong,et al."CCSpan: Mining closed contiguous sequential patterns".KNOWLEDGE-BASED SYSTEMS 89(2015):1-13.