Mining concise patterns on graph-connected itemsets

doi:10.1016/j.neucom.2018.03.084

	Mining concise patterns on graph-connected itemsets
	Zhang, Di 1; Zhang, Yunquan 1,2; Niu, Qiang 3; Qiu, Xingbao 4
	2019-04-07
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	336 页码:27-35
摘要	The itemset is a basic and usual form of data. People can obtain new insights into their business by discovering its implicit regularities through pattern mining. In some real applications, e.g., network alarm association, the itemsets usually have the following two characteristics: (1) the observed samples come from different entities, with inherent structural relationships implied in their static properties; (2) the samples are scarce, which may lead to incomplete pattern extraction. This paper considers how to efficiently find a concise set of patterns on such kind of data. Firstly, we use a graph to express the entities and their interconnections and propagate every sample to every node with a weight, determined by the pre-defined combination of kernel functions based on the similarities of the nodes and patterns. Next, the weight values can be naturally imported into the MDL-based filtering process and bring a differentiated pattern set for each node. Experiments show that the solution can outperform the global solution (trading all nodes as one) and isolated solution (removing all edges) on simulated and real data, and its effectiveness and scalability can be further verified in the application of large-scale network operation and maintenance. (C) 2018 Elsevier B.V. All rights reserved.
关键词	Pattern mining MDL Graph Diffusion kernel Maximal entropy random walk
DOI	10.1016/j.neucom.2018.03.084
收录类别	SCI
语种	英语
资助项目	NSF of China[11301420] ; NSF of Jiangsu Province[BK20150373] ; NSF of Jiangsu Province[BK20171237] ; Suzhou Science and Technology Program[SZS201613] ; XJTLU Key Programme Special Fund (KSF)
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000461358600004
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/4126
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Di
作者单位	1.Commun Univ China, Sch Comp Sci, Beijing 100024, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 3.Xian Jiaotong Liverpool Univ, Dept Math Sci, Suzhou 215123, Peoples R China 4.China Mobile Commun Corp, Beijing 100032, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Di,Zhang, Yunquan,Niu, Qiang,et al. Mining concise patterns on graph-connected itemsets[J]. NEUROCOMPUTING,2019,336:27-35.
APA	Zhang, Di,Zhang, Yunquan,Niu, Qiang,&Qiu, Xingbao.(2019).Mining concise patterns on graph-connected itemsets.NEUROCOMPUTING,336,27-35.
MLA	Zhang, Di,et al."Mining concise patterns on graph-connected itemsets".NEUROCOMPUTING 336(2019):27-35.