In this paper, we propose an on-demand distributed clustering algorithm for multi-hop packet radio networks. These types of networks, also known as ad hoc networks, are dynamic in ...
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Background: MapReduce is a parallel framework that has been used effectively to design largescale parallel applications for large computing clusters. In this paper, we evaluate th...
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Abstract. This paper proposes a new knowledge-based method for clustering metagenome short reads. The method incorporates biological knowledge in the clustering process, by means o...
Gianluigi Folino, Fabio Gori, Mike S. M. Jetten, E...