loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ahmad Ahdab and Marc Le Goc

Affiliation: Université Paul Cézanne, France

ISBN: 978-989-8425-23-2

Keyword(s): Machine Learning, Bayesian Network, Stochastic Representation, Data Mining, Knowledge Discovery.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Knowledge Acquisition ; Knowledge Discovery and Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

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 diagno ses a galvanization bat (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.175.201.14

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Ahdab A.; Le Goc M. and (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

@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},
}

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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.