The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
Network-analysis literature is rich in node-centrality measures that quantify the centrality of a node as a function of the (shortest) paths of the network that go through it. Exi...
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Supervised approaches to Data Mining are particularly appealing as they allow for the extraction of complex relations from data objects. In order to facilitate their application i...
Data mining is currently becoming an increasingly hot research field, but a large gap still remains between the research of data mining and its application in real-world business....