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Keys and Pseudo-Keys Detection for Web Datasets Cleansing and Interlinking

  • Manuel Atencia
  • Jérôme David
  • François Scharffe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7603)

Abstract

This paper introduces a method for analyzing web datasets based on key dependencies. The classical notion of a key in relational databases is adapted to RDF datasets. In order to better deal with web data of variable quality, the definition of a pseudo-key is presented. An RDF vocabulary for representing keys is also provided. An algorithm to discover keys and pseudo-keys is described. Experimental results show that even for a big dataset such as DBpedia, the runtime of the algorithm is still reasonable. Two applications are further discussed: (i) detection of errors in RDF datasets, and (ii) datasets interlinking.

Keywords

Relational Database Ontology Match Discriminability Threshold CEUR Workshop Proceeding Functional Approximate Dependency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Manuel Atencia
    • 1
    • 2
  • Jérôme David
    • 1
    • 3
  • François Scharffe
    • 4
  1. 1.INRIA & LIGFrance
  2. 2.Université de Grenoble 1France
  3. 3.Université de Grenoble 2France
  4. 4.Université de Montpellier 2 & LIRMMFrance

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