Discovering Dynamics using Bayesian Clustering

Authors

Paola Sebastiani, The Open University
Marco Ramoni, The Open University
Paul Cohen, University of Massachusetts - Amherst
John Warwick, University of Massachusetts - Amherst
James Davis, University of Massachusetts - Amherst

Publication Date

1999

Abstract

This paper introduces a Bayesian method for clustering dy-namic processes and applies it to the characterization of the dynamics of a military scenario. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to discover the most probable set of clusters capturing the different dynamics. To increase effciency, the method uses an entropy-based heuristic search strategy.

Comments

This paper was harvested from CiteSeer

Recommended Citation

Sebastiani, Paola; Ramoni, Marco; Cohen, Paul; Warwick, John; and Davis, James, "Discovering Dynamics using Bayesian Clustering" (1999). Computer Science Department Faculty Publication Series. 187.
Retrieved from https://scholarworks.umass.edu/cs_faculty_pubs/187