Index Based Hidden Outlier Detection in Metric Space
Joint Authors
Xu, Honglong
Liao, Hao
Zhang, He
Lu, Minhua
Chen, Guoliang
Mao, Rui
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-07-26
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Useless and noise information occupies large amount of big data, which increases our difficulty to extract worthy information.
Therefore outlier detection attracts much attention recently, but if two points are far from other points but are relatively close to each other, they are less likely to be detected as outliers because of their adjacency to each other.
In this situation, outliers are hidden by each other.
In this paper, we propose a new perspective of hidden outlier.
Experimental results show that it is more accurate than existing distance-based definitions of outliers.
Accordingly, we exploit a candidate set based hidden outlier detection (HOD) algorithm.
HOD algorithm achieves higher accuracy with comparable running time.
Further, we develop an index based HOD (iHOD) algorithm to get higher detection speed.
American Psychological Association (APA)
Xu, Honglong& Mao, Rui& Liao, Hao& Zhang, He& Lu, Minhua& Chen, Guoliang. 2016. Index Based Hidden Outlier Detection in Metric Space. Scientific Programming،Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1118379
Modern Language Association (MLA)
Xu, Honglong…[et al.]. Index Based Hidden Outlier Detection in Metric Space. Scientific Programming No. 2016 (2016), pp.1-14.
https://search.emarefa.net/detail/BIM-1118379
American Medical Association (AMA)
Xu, Honglong& Mao, Rui& Liao, Hao& Zhang, He& Lu, Minhua& Chen, Guoliang. Index Based Hidden Outlier Detection in Metric Space. Scientific Programming. 2016. Vol. 2016, no. 2016, pp.1-14.
https://search.emarefa.net/detail/BIM-1118379
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118379