Constellations and the unsupervised learning of graphs

In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an EM central clustering algorithm which builds prototypical graphs on the basis of fast matching with graph transformations. Our experiments, both with random graphs and in realistic situations (visual localization), show that our prototypes improve the set median graphs and also the prototypes derived from our previous incremental method. We also discuss how the method scales with a growing number of images.

Assessing participation in online discussion forums: a proposal for multidimensional analysis

This paper aims to assess the discussion forums being used in the programme Especialista Universitario online sobre Tecnologías de la Información y la Comunicación, taught at the University of Alicante, on the basis of the analysis model suggested by Kay (2004). In such a model, it is essential to represent graphically the forum activity so that the visual representation may improve analysis. This research has allowed reaching results which define the forum activity and has contributed with a proposal for multi analysis in the area of assessing participation in communication within online discussion forums.

Estadística Aplicada a los Recursos Marinos. MDS. Non Multidimensional Scaling Ordination

Análisis multivariante con MDS