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KDD
2012
ACM

Integrating community matching and outlier detection for mining evolutionary community outliers

11 years 6 months ago
Integrating community matching and outlier detection for mining evolutionary community outliers
Temporal datasets, in which data evolves continuously, exist in a wide variety of applications, and identifying anomalous or outlying objects from temporal datasets is an important and challenging task. Different from traditional outlier detection, which detects objects that have quite different behavior compared with the other objects, temporal outlier detection tries to identify objects that have different evolutionary behavior compared with other objects. Usually objects form multiple communities, and most of the objects belonging to the same community follow similar patterns of evolution. However, there are some objects which evolve in a very different way relative to other community members, and we define such objects as evolutionary community outliers. This definition represents a novel type of outliers considering both temporal dimension and community patterns. We investigate the problem of identifying evolutionary community outliers given the discovered communities from ...
Manish Gupta, Jing Gao, Yizhou Sun, Jiawei Han
Added 28 Sep 2012
Updated 28 Sep 2012
Type Journal
Year 2012
Where KDD
Authors Manish Gupta, Jing Gao, Yizhou Sun, Jiawei Han
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