Evaluating class assignment semantic redundancy on linked datasets
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ArticlePublication details: : , 2016Description: 1 archivo (1,9 MB)Subject(s): Online resources: 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.
| Item type | Current library | Call number | Status | Date due | Barcode |
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Biblioteca Fac.Informática | A0892 (Browse shelf(Opens below)) | Available | DIF-A0892 |
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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