: 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. ...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Dem...
Using microarray technology for genetic analysis in biological experiments requires computationally intensive tools to interpret results. The main objective here is to develop a â...
Saira Ali Kazmi, Yoo-Ah Kim, Baikang Pei, Ravi Nor...
Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. Often, t...
Matthew Perry, Amit P. Sheth, Farshad Hakimpour, P...