loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Mirna El Ghosh ; Cecilia Zanni-Merk ; Nicolas Delestre ; Jean-Philippe Kotowicz and Habib Abdulrab

Affiliation: Normandie Université, INSA Rouen, LITIS, 76000 Rouen, France

Keyword(s): Topic Ontologies, Topic Modeling, Open Knowledge Graphs, SPARQL.

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 q uality of Topic-OPA. (More)

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 18.224.52.108

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:
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) - KEOD; ISBN 978-989-758-474-9; ISSN 2184-3228, SciTePress, pages 275-282. DOI: 10.5220/0010147202750282

@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) - KEOD},
year={2020},
pages={275-282},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010147202750282},
isbn={978-989-758-474-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KEOD
TI - Topic-OPA: A Topic Ontology for Modeling Topics of Old Press Articles
SN - 978-989-758-474-9
IS - 2184-3228
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