Topic-OPA: A Topic Ontology for Modeling Topics of Old Press Articles

Mirna El Ghosh, Cecilia Zanni-Merk, Nicolas Delestre, Jean-Philippe Kotowicz, Habib Abdulrab

2020

Abstract

Topic ontologies are recently gaining much importance in several domains. Their purpose is to identify the themes necessary to describe the knowledge structure of an application domain. Meanwhile, their development from scratch is hard and time consuming task. This paper discusses the development a topic-specific ontology, named Topic-OPA, for modeling topics of old press articles. Topic-OPA is extracted from the open knowledge graph Wikidata by the application of a SPARQL-based fully automatic approach. The development process of Topic-OPA depends mainly on a set of disambiguated named entities representing the articles. Each named entity is unambiguously identified by a Wikidata URI. In contrast to existent topic ontologies, which are limited to taxonomies, the structure of Topic-OPA is composed of hierarchical and non-hierarchical schemes. The domain application of this work is the old french newspaper Le Matin. Finally, an evaluation process is performed to assess the structure quality of Topic-OPA.

Paper Citation

in Harvard Style

El Ghosh M., Zanni-Merk C., Delestre N., Kotowicz J. and Abdulrab H. (2020). Topic-OPA: A Topic Ontology for Modeling Topics of Old Press Articles. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD; ISBN 978-989-758-474-9, SciTePress, pages 275-282. DOI: 10.5220/0010147202750282

in Bibtex Style

@conference{keod20,
author={Mirna El Ghosh and Cecilia Zanni-Merk and Nicolas Delestre and Jean-Philippe Kotowicz and Habib Abdulrab},
title={Topic-OPA: A Topic Ontology for Modeling Topics of Old Press Articles},
booktitle={Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD},
year={2020},
pages={275-282},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010147202750282},
isbn={978-989-758-474-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 2: KEOD
TI - Topic-OPA: A Topic Ontology for Modeling Topics of Old Press Articles
SN - 978-989-758-474-9
AU - El Ghosh M.
AU - Zanni-Merk C.
AU - Delestre N.
AU - Kotowicz J.
AU - Abdulrab H.
PY - 2020
SP - 275
EP - 282
DO - 10.5220/0010147202750282
PB - SciTePress