In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
This paper deals with overlapping clustering, a trade off between crisp and fuzzy clustering. It has been motivated by recent applications in various domains such as information r...
Social networks are ubiquitous. The discovery of close-knit clusters in these networks is of fundamental and practical interest. Existing clustering criteria are limited in that cl...
Nina Mishra, Robert Schreiber, Isabelle Stanton, R...
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Recently published studies have shown that partitional clustering algorithms that optimize certain criterion functions, which measure key aspects of inter- and intra-cluster simil...