LEARNING DYNAMIC BAYESIAN NETWORKS WITH THE TOM4L PROCESS

Ahmad Ahdab, Marc Le Goc

Abstract

This paper addresses the problem of learning a Dynamic Bayesian Network from timed data without prior knowledge to the system. One of the main problems of learning a Dynamic Bayesian Network is building and orienting the edges of the network avoiding loops. The problem is more difficult when data are timed. This paper proposes a new algorithm to learn the structure of a Dynamic Bayesian Network and to orient the edges from the timed data contained in a given timed data base. This algorithm is based on an adequate representation of a set of sequences of timed data and uses an information based measure of the relations between two edges. This algorithm is a part of the Timed Observation Mining for Learning (TOM4L) process that is based on the Theory of the Timed Observations. The paper illustrates the algorithm with a theoretical example before presenting the results on an application on the Apache system of the Arcelor-Mittal Steel Group, a real world knowledge based system that diagnoses a galvanization bat

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Paper Citation


in Harvard Style

Ahdab A. and Le Goc M. (2010). LEARNING DYNAMIC BAYESIAN NETWORKS WITH THE TOM4L PROCESS . In Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT, ISBN 978-989-8425-23-2, pages 353-363. DOI: 10.5220/0002928603530363


in Bibtex Style

@conference{icsoft10,
author={Ahmad Ahdab and Marc Le Goc},
title={LEARNING DYNAMIC BAYESIAN NETWORKS WITH THE TOM4L PROCESS},
booktitle={Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT,},
year={2010},
pages={353-363},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002928603530363},
isbn={978-989-8425-23-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT,
TI - LEARNING DYNAMIC BAYESIAN NETWORKS WITH THE TOM4L PROCESS
SN - 978-989-8425-23-2
AU - Ahdab A.
AU - Le Goc M.
PY - 2010
SP - 353
EP - 363
DO - 10.5220/0002928603530363