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Authors: Zakaria Mejdoul and Gaëlle Lortal

Affiliation: Thales Research & Technology, Palaiseau, France

Keyword(s): Ontology, Reasoner, Controlled Natural Language, Verbalization, Sentences Generation.

Abstract: The Semantic Web (SW) is an enhancement to the World Wide Web (WWW). It allows Humans to find, share and integrate information more easily. One of the Knowledge Representation technologies related to the SW standards is the ontology, which is an inventory of knowledge defining a universal or specific domain. Ontology construction requires expertise related to logics and to the expert domain the SW application is applied to. We aim to enable ontology wide adoption by bringing the end-users closer to their own ontology building choices, providing them with the possibility to build their ontology, to validate its consistency and to formally represent their knowledge without formal methods knowledge. In this paper, we detail our tool architecture combining SW technologies and Natural Language Generation (NLG) to support users in creating consistent ontologies.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Mejdoul, Z. and Lortal, G. (2022). GLUON: A Reasoning-based and Natural Language Generation-based System to Explicit Ontology Design Choices. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD; ISBN 978-989-758-614-9; ISSN 2184-3228, SciTePress, pages 228-236. DOI: 10.5220/0011587900003335

@conference{keod22,
author={Zakaria Mejdoul. and Gaëlle Lortal.},
title={GLUON: A Reasoning-based and Natural Language Generation-based System to Explicit Ontology Design Choices},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD},
year={2022},
pages={228-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011587900003335},
isbn={978-989-758-614-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD
TI - GLUON: A Reasoning-based and Natural Language Generation-based System to Explicit Ontology Design Choices
SN - 978-989-758-614-9
IS - 2184-3228
AU - Mejdoul, Z.
AU - Lortal, G.
PY - 2022
SP - 228
EP - 236
DO - 10.5220/0011587900003335
PB - SciTePress

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