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...
Current research in indexing and mining time series data has produced many interesting algorithms and representations. However, it has not led to algorithms that can scale to the ...
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
In this paper, we discuss a problem of finding risk patterns in medical data. We define risk patterns by a statistical metric, relative risk, which has been widely used in epidemi...
Jiuyong Li, Ada Wai-Chee Fu, Hongxing He, Jie Chen...
In several organizations, it has become increasingly popular to document and log the steps that makeup a typical business process. In some situations, a normative workflow model o...