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	An efficient algorithm for mining the top-k high utility itemsets, using novel threshold raising and pruning strategies
	Duong, QH; Liao, B; Fournier-Viger, P; Dam, TL
刊名	Knowledge-Based Systems
	2016
卷号	Vol.104页码:106-122
关键词	High utility itemset mining Top-k mining Threshold raising strategies Co-occurrence pruning Transitive extension pruning Coverage
URL标识	查看原文
公开日期	[db:dc_date_available]
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/6067117
专题	湖南大学
作者单位	1.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Hunan, Peoples R China 2.Harbin Inst Technol, Sch Nat Sci & Humanities, Shenzhen Grad Sch, Shenzhen 518055, Guangdong, Peoples R China 3.Hanoi Univ Ind, Fac Informat Technol, Hanoi, Vietnam
推荐引用方式 GB/T 7714	Duong, QH,Liao, B,Fournier-Viger, P,et al. An efficient algorithm for mining the top-k high utility itemsets, using novel threshold raising and pruning strategies[J]. Knowledge-Based Systems,2016,Vol.104:106-122.
APA	Duong, QH,Liao, B,Fournier-Viger, P,&Dam, TL.(2016).An efficient algorithm for mining the top-k high utility itemsets, using novel threshold raising and pruning strategies.Knowledge-Based Systems,Vol.104,106-122.
MLA	Duong, QH,et al."An efficient algorithm for mining the top-k high utility itemsets, using novel threshold raising and pruning strategies".Knowledge-Based Systems Vol.104(2016):106-122.

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