Temporal data mining aims at finding patterns in historical data. Our work proposes an approach to extract temporal patterns from data to predict the occurrence of target events,...
A neural network based clustering method for the analysis of soft handovers in 3G network is introduced. The method is highly visual and it could be utilized in explorative analys...
Presence-absence (0-1) observations are special in that often the absence of evidence is not evidence of absence. Here we develop an independent factor model, which has the unique...
—Networks are widely used in modeling relational data often comprised of thousands of nodes and edges. This kind of data alone implies a challenge for its visualization as it is ...
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...