The paper introduces a framework for clustering data objects in a similarity-based context. The aim is to cluster objects into a given number of classes without imposing a hard pa...
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
We show that an important and computationally challenging solution space feature of the graph coloring problem (COL), namely the number of clusters of solutions, can be accurately...
: This paper investigates organization problems of large wireless sensor networks. In spite of their random deployment, nodes have to organize themselves as energy efficient as pos...
Phrase has been considered as a more informative feature term for improving the effectiveness of document clustering. In this paper, we propose a phrase-based document similarity t...