In this paper a fuzzy quantization dequantization criterion is used to propose an evaluation technique to determine the appropriate clustering algorithm suitable for a particular ...
— Clustering is a pivotal building block in many data mining applications and in machine learning in general. Most clustering algorithms in the literature pertain to off-line (or...
Steven Young, Itamar Arel, Thomas P. Karnowski, De...
A novel breadth-first based structural clustering method for graphs is proposed. Clustering is an important task for analyzing complex networks such as biological networks, World ...
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Among various document clustering algorithms that have been proposed so far, the most useful are those that automatically reveal the number of clusters and assign each target docum...
Eugene Levner, David Pinto, Paolo Rosso, David Alc...