Tech Report

Discovering Dynamics using Bayesian Clustering

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.

ID: kmi-99-04

Date: 1999

Author(s): Paola Sebastiani, Marco Ramoni, Paul Cohen, John Warwick and James Davis

Resources:
Download PDF

View By

Other Publications

CONTACT US

Knowledge Media Institute
The Open University
Walton Hall
Milton Keynes
MK7 6AA
United Kingdom

Tel: +44 (0)1908 653800

Fax: +44 (0)1908 653169

Email: KMi Support

COMMENT

If you have any comments, suggestions or general feedback regarding our website, please email us at the address below.

Email: KMi Development Team