: Temporal data mining is concerned with the analysis of temporal data and finding temporal patterns, regularities, trends, clusters in sets of temporal data. Wavelet transform pro...
The evolution of dependencies in information hierarchies can be modeled by sequences of compound digraphs with edge weights. In this paper we present a novel approach to visualize...
Diffusion tensor imaging is a magnetic resonance imaging method which has gained increasing importance in neuroscience and especially in neurosurgery. It acquires diffusion proper...
Frank Enders, Natascha Sauber, Dorit Merhof, Peter...
In this paper, we introduce a new method, GraphScape, to visualize multivariate networks, i.e., graphs with multivariate data associated with their nodes. GraphScape adopts a land...
Kai Xu 0003, Andrew Cunningham, Seok-Hee Hong, Bru...
Accessing data stored in persistent memory represents a bottleneck for current visual exploration applications. Semantic caching of frequent queries at the client-side along with ...
Punit R. Doshi, Geraldine E. Rosario, Elke A. Rund...