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	An efficient algorithm for mining the top-k high utility itemsets, using novel threshold raising and pruning strategies
	Duong, Q.-H.; Liao, B.; Fournier-Viger, P.; Dam, T.-L.
刊名	Knowledge-Based Systems
	2016
卷号	Vol.104页码:106-122
关键词	Co-occurrence pruning Coverage High utility itemset mining Threshold raising strategies Top-k mining Transitive extension pruning
ISSN号	0950-7051
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/6070791
专题	湖南大学
作者单位	1.a College of Computer Science and Electronic Engineering, Hunan University, Changsha, China 2.School of Natural Sciences and Humanities, Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, Guangdong, China 3.Faculty of Information Technology, Hanoi University of Industry, Hanoi, Viet Nam
推荐引用方式 GB/T 7714	Duong, Q.-H.,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, Q.-H.,Liao, B.,Fournier-Viger, P.,&Dam, T.-L..(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, Q.-H.,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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