Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 27, Issue 4, Pages 681-697Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2004.07.002
Keywords
outlier; data mining; CRM; direct marketing
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Outliers, or commonly referred to as exceptional cases, exist in many real-world databases. Detection of such outliers is important for many applications and has attracted much attention from the data mining research community recently. However, most existing methods are designed for mining outliers from a single dataset without considering the class labels of data objects. In this paper, we consider the class outlier detection problem 'given a set of observations with class labels, find those that arouse suspicions, taking into account the class labels'. By generalizing two pioneer contributions [Proc WAIM02 (2002); Proc SSTD03] in this field, we develop the notion of class outlier and propose practical solutions by extending existing outlier detection algorithms to this case. Furthermore, its potential applications in CRM (customer relationship management) are also discussed. Finally, the experiments in real datasets show that our method can find interesting outliers and is of practical use. (C) 2004 Elsevier Ltd. All rights reserved.
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