The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
The growing availability of mobile devices produces an enormous quantity of personal tracks which calls for advanced analysis methods capable of extracting knowledge out of massiv...
A fundamental task of data analysis is comprehending what distinguishes clusters found within the data. We present the problem of mining distinguishing sets which seeks to find s...
Linking or matching databases is becoming increasingly important in many data mining projects, as linked data can contain information that is not available otherwise, or that woul...
Abstract. We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation...