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Communication dans un congrès

Targeted Linked-Data Extractor

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.

Type de document :
Communication dans un congrès
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https://hal.univ-angers.fr/hal-03256738
Contributeur : Okina Université d'Angers <>
Soumis le : jeudi 10 juin 2021 - 14:15:52
Dernière modification le : mardi 22 juin 2021 - 03:41:11

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Citation

Pierre Maillot, Thomas Raimbault, David Genest, Stephane Loiseau. Targeted Linked-Data Extractor. The 6th International Conference on Agents and Artificial Intelligence (ICAART 2014), 2014, Angers, France. pp.336-341, ⟨10.5220/0004758503360341⟩. ⟨hal-03256738⟩

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