Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
Many data are modeled as tensors, or multi dimensional arrays. Examples include the predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the Web g...
U. Kang, Evangelos E. Papalexakis, Abhay Harpale, ...
The Knowledge Discovery Toolbox (KDT) enables domain experts to perform complex analyses of huge datasets on supercomputers using a high-level language without grappling with the ...
Understanding the impact of individual and task differences on search result page examination strategies is important in developing improved search engines. Characterizing these e...
Georg Buscher, Ryen W. White, Susan T. Dumais, Jef...
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...