Abstract: Spatial data mining algorithms heavily depend on the efficient processing of neighborhood relations since the neighbors of many objects have to be investigated in a singl...
Martin Ester, Alexander Frommelt, Hans-Peter Krieg...
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
We consider the problem of aggregation for uncertain and imprecise data. For such data, we define aggregation operators and use them to provide information on properties and patte...
Cancer-related investigations have long been in the limelight of biomedical research. Years of effort from scientists and doctors worldwide have generated large amounts of data at...
Hong Li, Ying He, Guohui Ding, Chuan Wang, Lu Xie,...
ions in Process Mining: A Taxonomy of Patterns R.P. Jagadeesh Chandra Bose1,2 and Wil M.P. van der Aalst1 1 Department of Mathematics and Computer Science, University of Technology...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...