Some issues about outlier detection in rough set theory

doi:10.1016/j.eswa.2008.06.019

	Some issues about outlier detection in rough set theory
	Jiang, Feng 1; Sui, Yuefei 2; Cao, Cungen 2
	2009-04-01
发表期刊	EXPERT SYSTEMS WITH APPLICATIONS
ISSN	0957-4174
卷号	36 期号:3 页码:4680-4687
摘要	"One person's noise is another person's signal" (Knorr, E., Ng, R. (1998). Algorithms for mining distance-based outliers in large datasets. In Proceedings of the 24th VLDB conference, New York (pp. 392-403)). In recent years, much attention has been given to the problem of outlier detection, whose aim is to detect outliers - objects which behave in an unexpected way or have abnormal properties. Detecting such outliers is important for many applications such as criminal activities in electronic commerce, computer intrusion attacks, terrorist threats, agricultural pest infestations, etc. And outlier detection is critically important in the information-based society. In this paper, we discuss some issues about outlier detection in rough set theory which emerged about 20 years ago, and is nowadays a rapidly developing branch of artificial intelligence and soft computing. First, we propose a novel definition of outliers in information systems of rough set theory - sequence-based outliers. An algorithm to find such outliers in rough set theory is also given. The effectiveness of sequence-based method for outlier detection is demonstrated on two publicly available databases. Second, we introduce traditional distance-based outlier detection to rough set theory and discuss the definitions of distance metrics for distance-based outlier detection in rough set theory. (C) 2008 Elsevier Ltd. All rights reserved.
关键词	Outlier detection Rough sets Distance metric KDD
DOI	10.1016/j.eswa.2008.06.019
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation[60641010] ; Natural Science Foundation[60496326] ; Natural Science Foundation[60573063] ; Natural Science Foundation[60573064] ; National 863 Programme[2007AAO1Z325] ; National 973 Programme[2003CB317008] ; National 973 Programme[G1999032701]
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:000263584100063
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：55[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/11848
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Jiang, Feng
作者单位	1.Qingdao Univ Sci & Technol, Coll Informat Sci & Technol, Qingdao 266061, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Jiang, Feng,Sui, Yuefei,Cao, Cungen. Some issues about outlier detection in rough set theory[J]. EXPERT SYSTEMS WITH APPLICATIONS,2009,36(3):4680-4687.
APA	Jiang, Feng,Sui, Yuefei,&Cao, Cungen.(2009).Some issues about outlier detection in rough set theory.EXPERT SYSTEMS WITH APPLICATIONS,36(3),4680-4687.
MLA	Jiang, Feng,et al."Some issues about outlier detection in rough set theory".EXPERT SYSTEMS WITH APPLICATIONS 36.3(2009):4680-4687.