Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
— We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of p...
Background: Detecting groups of functionally related proteins from their amino acid sequence alone has been a long-standing challenge in computational genome research. Several clu...
Tobias Wittkop, Jan Baumbach, Francisco P. Lobo, S...
The assessment of chemical similarity between molecules is a basic operation in chemoinformatics, a computational area concerning with the manipulation of chemical structural info...