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Semantic Web Datatype Inference: Towards Better RDF Matching

  • Irvin Dongo
  • Yudith Cardinale
  • Firas Al-Khalil
  • Richard Chbeir
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10570)

Abstract

In the context of RDF document matching/integration, the datatype information, which is related to literal objects, is an important aspect to be analyzed in order to better determine similar RDF documents. In this paper, we propose a datatype inference process based on four steps: (i) predicate information analysis (i.e., deduce the datatype from existing range property); (ii) analysis of the object value itself by a pattern-matching process (i.e., recognize the object lexical-space); (iii) semantic analysis of the predicate name and its context; and (iv) generalization of numeric and binary datatypes to ensure the integration. We evaluated the performance and the accuracy of our approach with datasets from DBpedia. Results show that the execution time of the inference process is linear and its accuracy can increase up to 97.10%.

Keywords

Datatype analysis Datatype inference XML RDF Semantic Web 

Notes

Acknowledgments

FINCyT/INNOVATE Peru - N 104-FINCyT-BDE-2014.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Irvin Dongo
    • 1
  • Yudith Cardinale
    • 2
  • Firas Al-Khalil
    • 3
  • Richard Chbeir
    • 1
  1. 1.Univ Pau and Pays Adour, LIUPPA, EA3000AngletFrance
  2. 2.Dpto. de Computación y Tecnología de la InformaciónUniv. Simón BolívarCaracasVenezuela
  3. 3.University College Cork, CRCTCCorkIreland

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