Tech Reports
Tech Report kmi-99-04 Abstract
Discovering Dynamics using Bayesian Clustering
Techreport ID: kmi-99-04
Date: 1999
Author(s): Paola Sebastiani, Marco Ramoni, Paul Cohen, John Warwick and James Davis
This paper introduces a Bayesian method for clustering dynamic 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 efficiency, the method uses an entropy-based heuristic search strategy. 1. Department of Statistics, The Open University. 2. Knowledge Media Institute, The Open University. 3. Department of Computer Science, University of Massachusetts at Amherst.
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