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.

References

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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