Graph clustering has become ubiquitous in the study of relational data sets. We examine two simple algorithms: a new graphical adaptation of the k-medoids algorithm and the Girvan...
A promising approach to compare two graph clusterings is based on using measurements for calculating the distance between them. Existing measures either use the structure of cluste...
Abstract. In this paper we describe several new clustering algorithms for nodes in a mobile ad hoc network. The main contribution is to generalize the cluster definition and forma...
Geng Chen, Fabian Garcia Nocetti, Julio Solano-Gon...
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
Network visualisations use clustering approaches to simplify the presentation of complex graph structures. We present a novel application of clustering algorithms, which controls ...