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KAIS
2007

Capabilities of outlier detection schemes in large datasets, framework and methodologies

9 years 1 months ago
Capabilities of outlier detection schemes in large datasets, framework and methodologies
Abstract. Outlier detection is concerned with discovering exceptional behaviors of objects. Its theoretical principle and practical implementation lay a foundation for some important applications such as credit card fraud detection, discovering criminal behaviors in e-commerce, discovering computer intrusion, etc. In this paper, we first present a unified model for several existing outlier detection schemes, and propose a compatibility theory, which establishes a framework for describing the capabilities for various outlier formulation schemes in terms of matching users’ intuitions. Under this framework we show that the density-based scheme is more powerful than the distance-based scheme when a dataset contains patterns with diverse characteristics. The densitybased scheme, however, is less effective when the patterns are of comparable densities with the outliers. We then introduce a connectivity-based scheme that improves the effectiveness of the density-based scheme when a patt...
Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, David W
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2007
Where KAIS
Authors Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, David W. Cheung
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