With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
In this article, we evaluate the performance of three clustering algorithms, hard K-Means, single linkage, and a simulated annealing (SA) based technique, in conjunction with four ...
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...
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Abstract. Cluster validation to determine the right number of clusters is an important issue in clustering processes. In this work, a strategy to address the problem of cluster val...