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Evaluating class assignment semantic redundancy on linked datasets

By:

Mendoza, Leandro

Contributor(s):

Díaz, Alicia Viviana

Material type: Article

ArticlePublication details: : , 2016Description: 1 archivo (1,9 MB)Subject(s):

Online resources:

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Summary: In this work we address the concept of semantic redundancy in linked datasets considering class assignment assertions. We discuss how redundancy can be evaluated as well as the relationship between redundancy and three class hierarchy aspects: the number of instances a class has, number of class descendants and class depth. Finally, we performed an evaluation on the DBpedia dataset using SPARQL queries for data redundancy checks.

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Item type	Current library	Call number	Status	Date due	Barcode
Capítulo de libro	Biblioteca Fac.Informática	A0892 (Browse shelf(Opens below))	Available		DIF-A0892

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Formato de archivo PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)

In this work we address the concept of semantic redundancy in linked datasets considering class assignment assertions. We discuss how redundancy can be evaluated as well as the relationship between redundancy and three class hierarchy aspects: the number of instances a class has, number of class descendants and class depth. Finally, we performed an evaluation on the DBpedia dataset using SPARQL queries for data redundancy checks.

Annual International Symposium on Information Management and Big Data (3er : 2016 : Cuzco, Perú)

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