RDF Query Relaxation Strategies Based on Failure Causes

  • Géraud Fokou
  • Stéphane JeanEmail author
  • Allel Hadjali
  • Mickaël Baron
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9678)


Recent advances in Web-information extraction have led to the creation of several large Knowledge Bases (KBs). Querying these KBs often results in empty answers that do not serve the users’ needs. Relaxation of the failing queries is one of the cooperative techniques used to retrieve alternative results. Most of the previous work on RDF query relaxation compute a set of relaxed queries and execute them in a similarity-based ranking order. Thus, these approaches relax an RDF query without knowing its failure causes (FCs). In this paper, we study the idea of identifying these FCs to speed up the query relaxation process. We propose three relaxation strategies based on various information levels about the FCs of the user query and of its relaxed queries as well. A set of experiments conducted on the LUBM benchmark show the impact of our proposal in comparison with a state-of-the-art algorithm.


Execution Time SPARQL Query Relaxation Strategy Triple Pattern Initial Query 
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 International Publishing Switzerland 2016

Authors and Affiliations

  • Géraud Fokou
    • 1
  • Stéphane Jean
    • 1
    Email author
  • Allel Hadjali
    • 1
  • Mickaël Baron
    • 1
  1. 1.LIAS/ISAE-ENSMAUniversity of PoitiersFuturoscope CedexFrance

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