Data-Driven RDF Property Semantic-Equivalence Detection Using NLP Techniques

  • Mariano Rico
  • Nandana Mihindukulasooriya
  • Asunción Gómez-Pérez
Conference paper

DOI: 10.1007/978-3-319-49004-5_51

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10024)
Cite this paper as:
Rico M., Mihindukulasooriya N., Gómez-Pérez A. (2016) Data-Driven RDF Property Semantic-Equivalence Detection Using NLP Techniques. In: Blomqvist E., Ciancarini P., Poggi F., Vitali F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science, vol 10024. Springer, Cham

Abstract

DBpedia extracts most of its data from Wikipedia’s infoboxes. Manually-created “mappings” link infobox attributes to DBpedia ontology properties (dbo properties) producing most used DBpedia triples. However, infoxbox attributes without a mapping produce triples with properties in a different namespace (dbp properties). In this position paper we point out that (a) the number of triples containing dbp properties is significant compared to triples containing dbo properties for the DBpedia instances analyzed, (b) the SPARQL queries made by users barely use both dbp and dbo properties simultaneously, (c) as an exploitation example we show a method to automatically enhance SPARQL queries by using syntactic and semantic similarities between dbo properties and dbp properties.

Keywords

SPARQL query Query enhancement DBpedia Spanish DBpedia Property mapping 

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Mariano Rico
    • 1
  • Nandana Mihindukulasooriya
    • 1
  • Asunción Gómez-Pérez
    • 1
  1. 1.Ontology Engineering GroupUniversidad Politécnica de MadridMadridSpain

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