Authors
Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, David W Cheung
Publication date
2002
Conference
Advances in Knowledge Discovery and Data Mining: 6th Pacific-Asia Conference, PAKDD 2002 Taipei, Taiwan, May 6–8, 2002 Proceedings 6
Pages
535-548
Publisher
Springer Berlin Heidelberg
Description
Outlier detection is concerned with discovering exceptional behaviors of objects in data sets. It is becoming a growingly useful tool in applications such as credit card fraud detection, discovering criminal behaviors in e-commerce, identifying computer intrusion, detecting health problems, etc. In this paper, we introduce a connectivity-based outlier factor (COF) scheme that improves the effectiveness of an existing local outlier factor (LOF) scheme when a pattern itself has similar neighbourhood density as an outlier. We give theoretical and empirical analysis to demonstrate the improvement in effectiveness and the capability of the COF scheme in comparison with the LOF scheme.
Total citations
Scholar articles
J Tang, Z Chen, AWC Fu, DW Cheung - Advances in Knowledge Discovery and Data Mining …, 2002