A Cognition-inspired Knowledge Representation Approach for Knowledge-based Interpretation Systems

Joel Luis Carbonera, Mara Abel

2015

Abstract

We propose a hybrid approach for knowledge representation that combines classic representations (such as rules and ontologies) with cognitively plausible representations, such as prototypes and exemplars. The resulting framework can be used for developing knowledge-based systems that combine knowledge-driven and data-driven techniques. We also present how this approach can be used for developing an application for interpretation of depositional processes in Petroleum Geology.

Paper Citation

in Harvard Style

Carbonera J. and Abel M. (2015). A Cognition-inspired Knowledge Representation Approach for Knowledge-based Interpretation Systems . In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 644-649. DOI: 10.5220/0005467106440649

in Bibtex Style

@conference{iceis15,
author={Joel Luis Carbonera and Mara Abel},
title={A Cognition-inspired Knowledge Representation Approach for Knowledge-based Interpretation Systems},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={644-649},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005467106440649},
isbn={978-989-758-096-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Cognition-inspired Knowledge Representation Approach for Knowledge-based Interpretation Systems
SN - 978-989-758-096-3
AU - Carbonera J.
AU - Abel M.
PY - 2015
SP - 644
EP - 649
DO - 10.5220/0005467106440649