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Authors: Pierre Maillot 1 ; Thomas Raimbault 1 ; David Genest 2 and Stephane Loiseau 2

Affiliations: 1 Pôle Universitaire Léonard de Vinci, France ; 2 Faculté des Sciences d’Angers, France

Keyword(s): Semantic Web, Linked Data, Extraction

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Collaboration and e-Services ; e-Business ; Enterprise Engineering ; Enterprise Information Systems ; Enterprise Ontologies ; Formal Methods ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Ontologies ; Semantic Web ; Simulation and Modeling ; Soft Computing ; Symbolic Systems

Abstract: The Linked Data Cloud is too big to be locally manipulated by standard computers and all use-cases doesn’t need to manipulate the whole cloud. To get exactly what is needed for a specific use-case, we need to obtain the specific parts from each bases of the Linked Data Cloud. This paper proposes a method to smartly extract a sub-part of the Linked Data Cloud driving by a list of resources called seeds. This method consist of extracting data starting from seed resources and recursively expanding the extraction to their neighbours.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Maillot, P.; Raimbault, T.; Genest, D. and Loiseau, S. (2014). Targeted Linked-Data Extractor. In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-015-4; ISSN 2184-433X, SciTePress, pages 336-341. DOI: 10.5220/0004758503360341

@conference{icaart14,
author={Pierre Maillot. and Thomas Raimbault. and David Genest. and Stephane Loiseau.},
title={Targeted Linked-Data Extractor},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2014},
pages={336-341},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004758503360341},
isbn={978-989-758-015-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Targeted Linked-Data Extractor
SN - 978-989-758-015-4
IS - 2184-433X
AU - Maillot, P.
AU - Raimbault, T.
AU - Genest, D.
AU - Loiseau, S.
PY - 2014
SP - 336
EP - 341
DO - 10.5220/0004758503360341
PB - SciTePress