Targeted Linked-Data Extractor

Pierre Maillot, Thomas Raimbault, David Genest, Stephane Loiseau

2014

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.

Paper Citation

in Harvard Style

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, pages 336-341. DOI: 10.5220/0004758503360341

in Bibtex Style

@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},
}

in EndNote Style

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
AU - Maillot P.
AU - Raimbault T.
AU - Genest D.
AU - Loiseau S.
PY - 2014
SP - 336
EP - 341
DO - 10.5220/0004758503360341