Edwin Zarrazola

A Divide-and-Link algorithm for hierarchical clustering in networks

This paper introduces a hierarchical clustering algorithm in networks based upon a first divisive stage to break the graph and a second linking stage which is used to join nodes. As a particular case, this algorithm is applied to the specific problem of community detection in social networks, where a betweenness measure is considered for the divisive criterion and a similarity measure associated to data is used for the linking criterion. We show that this algorithm is very flexible as well as quite competitive (from both a performance and a computational complexity point of view) in relation with a set of state-of-the-art algorithms. Furthermore, the output given by the proposed algorithm allows to show in a dynamic and interpretable way the evolution of how the groups are split in the network.

A New concept of of fuzzy image segmentation

A crisp image segmentation can be characterized in terms of the set of edges that separates the adjacent regions of the segmentation. Based on these edges, an alternative way to define a fuzzy image segmentation is introduced in this paper. In this sense, the notion of fuzzy image segmentation is characterized by means of a fuzzy set over the set of edges, which could in this way be understood as the fuzzy boundary of the image. Also, an algorithm to construct this fuzzy boundary is provided based on the relations that exist

Multivariate Macdonald Distribution and Its Properties

We give multivariate generalization of Macdonald distribution and study several of its properties. We also define the multivariate Macdonald-gamma distribution and derive a number of results pertaining to it.