We address the problem of capturing and tracking local correlations among time evolving time series. Our approach is based on comparing the local auto-covariance matrices (via the...
We present a set of techniques and design principles for the visualization of large dynamic software logs consisting of attributed change events, such as obtained from instrumenti...
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Many data sets are incomplete. For correct analysis of such data, one can either use algorithms that are designed to handle missing data or use imputation. Imputation has the bene...
Spatial data mining, i.e., discovery of interesting, implicit knowledge in spatial databases, is an important task for understanding and use of spatial data- and knowledge-bases. I...