We explore in this paper the efficient clustering of item data. Different from those of the traditional data, the features of item data are known to be of high dimensionality and...
Gene clustering, the process of grouping related genes in the same cluster, is at the foundation of different genomic studies that aim at analyzing the function of genes. Microarr...
Xiang Xiao, Ernst R. Dow, Russell C. Eberhart, Zin...
: We propose a set of statistical metrics for making a comprehensive, fair, and insightful evaluation of features, clustering algorithms, and distance measures in representative sa...
Surface-based techniques for protein comparison and classification typically require a compact surface representation, capable of effectively condensing its description. In this p...
Alessandra Lumini, Lorenzo Baldacci, Matteo Golfar...
The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...