Multi-entity Bayesian Networks for Treasuring the Intangible Cultural Heritage

Giannis Chantas, Spiros Nikolopoulos, Ioannis Kompatsiaris

2014

Abstract

In this paper, we propose the use of Multi-entity Bayesian networks (MEBNs) for modeling the knowledge and analyzing the content pertaining to the domain of Intangible Cultural Heritage (ICH). MEBNs provide a rigorous knowledge representation framework in conjunction with reasoning and probabilistic inference capabilities. There are mainly two reasons motivating the use of MEBNs in the domain of ICH. The first is that MEBNs extend first-order logic with the ability to model uncertainty. The second reason is the capability of MEBN to adapt to specific situations by providing custom, situation specific Bayesian networks. Finally, we use an example to demonstrate the potential efficiency of MEBNs in the domain of ICH.

Paper Citation

in Harvard Style

Chantas G., Nikolopoulos S. and Kompatsiaris I. (2014). Multi-entity Bayesian Networks for Treasuring the Intangible Cultural Heritage . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: IAMICH, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 796-802. DOI: 10.5220/0004875407960802

in Bibtex Style

@conference{iamich14,
author={Giannis Chantas and Spiros Nikolopoulos and Ioannis Kompatsiaris},
title={Multi-entity Bayesian Networks for Treasuring the Intangible Cultural Heritage},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: IAMICH, (VISIGRAPP 2014)},
year={2014},
pages={796-802},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004875407960802},
isbn={978-989-758-004-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: IAMICH, (VISIGRAPP 2014)
TI - Multi-entity Bayesian Networks for Treasuring the Intangible Cultural Heritage
SN - 978-989-758-004-8
AU - Chantas G.
AU - Nikolopoulos S.
AU - Kompatsiaris I.
PY - 2014
SP - 796
EP - 802
DO - 10.5220/0004875407960802