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Benchmarking Applied to Semantic Conceptual Models of Linked Financial Data

  • José Luis Sánchez-Cervantes
  • Lisbeth Rodríguez-Mazahua
  • Giner Alor-Hernández
  • Cuauhtémoc Sánchez-Ramírez
  • Jorge Luis García-Alcaráz
  • Emilio Jimenez-Macias
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9416)

Abstract

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 knowledge-based 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.

Keywords

Conceptual modeling Linked data Performance Semantics SPARQL 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • José Luis Sánchez-Cervantes
    • 1
  • Lisbeth Rodríguez-Mazahua
    • 1
  • Giner Alor-Hernández
    • 1
  • Cuauhtémoc Sánchez-Ramírez
    • 1
  • Jorge Luis García-Alcaráz
    • 2
  • Emilio Jimenez-Macias
    • 3
  1. 1.Division of Research and Postgraduate StudiesInstituto Tecnológico de OrizabaOrizabaMexico
  2. 2.Department of Industrial EngineeringUniversidad Autónoma de Ciudad JuárezCiudad JuárezMexico
  3. 3.Department of Electrical EngineeringUniversity of La RiojaLogroñoSpain

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