Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection met...
In the era of information explosion, structured data emerge on a large scale. As a description of structured data, network has drawn attention of researchers in many subjects. Netw...
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
Detecting outliers in a large set of data objects is a major data mining task aiming at finding different mechanisms responsible for different groups of objects in a data set. All...
Hans-Peter Kriegel, Matthias Schubert, Arthur Zime...
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...