Benchmarking applied to semantic conceptual models of linked financial data
- Sánchez-Cervantes, J.L. 3
- Rodríguez-Mazahua, L. 3
- Alor-Hernández, G. 3
- Sánchez-Ramírez, C. 3
- García-Alcaráz, J.L. 2
- Jimenez-Macias, E. 1
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1
Universidad de La Rioja
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2
Universidad Autónoma de Ciudad Juárez
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3
Instituto Tecnologico de Orizaba
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ISSN: 0302-9743
Año de publicación: 2015
Volumen: 9416
Páginas: 289-298
Tipo: Artículo
Otras publicaciones en: Lecture Notes in Computer Science
Resumen
Semantic modeling plays a central role in knowledge-based systems where information sharing and integration is a primary objective. Ontology and metadata description languages such as OWL (Web Ontology Language) and RDF(S) (Resource Description Framework Schema) are commonly the most used for representing semantic models and data. The graph-like structure adopted for semantic metadata representation allows simple and expressive queries by using SPARQL-based subgraph matching. While performance of such knowledgebased systems depends on multiple factors, in this work we present a mechanism to properly choice a semantic modeling pattern in order to significantly reduce the data query execution time. Based on this understanding, this work proposes a comparative analysis of different conceptual modeling approaches on the basis of financial domain. In order to show the efficiency/accuracy of our approach, an evaluation of SPARQL-based queries was performed against different modeled datasets. © Springer International Publishing Switzerland 2015.