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CaRT: Framework for Semantic Query Correction and Relaxation

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Digital Economy. Emerging Technologies and Business Innovation (ICDEc 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 358))

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Abstract

With the emergence of the resource description framework (RDF) graphs, the SPARQL query processing on the large-scale RDF graph has become a more challenging problem. However, the efficiency of SPARQL query is difficult to reach and there are several issues that may arise. In our work, we address the problem of the no answer query. Many approaches are proposed to deal with this problem. These approaches used in generally relaxation methods to help user in finding alternative answers when their queries fail or do not return the expected answers. However, the majority of the proposed works don’t detect and show to the user the cause of failure. This paper presents a Correct-and-Relax Triples (CaRT) framework designed to facilitate the exploitation of large knowledge base. Our framework proposes a new relaxation method that detects and corrects only the failed triples of a failed SPARQL query. We conducted comprehensive experiments on a benchmark RDF dataset and demonstrated the performance of our approach by improving the efficiency of the SPRQL query.

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Notes

  1. 1.

    swat.cse.lehigh.edu/onto/univ-bench.owl.

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Authors and Affiliations

  1. Higher School of Digital Economy, Manouba University, Manouba, Tunisia

    Oumaima Mbazaia & Karim Kamoun

Authors
  1. Oumaima Mbazaia
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  2. Karim Kamoun
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Corresponding authors

Correspondence to Oumaima Mbazaia or Karim Kamoun .

Editor information

Editors and Affiliations

  1. ESEN, University of Manouba, Manouba, Tunisia

    Rim Jallouli

  2. ESEN, University of Manouba, Manouba, Tunisia

    Mohamed Anis Bach Tobji

  3. Université de Sherbrooke, Sherbrooke, QC, Canada

    Deny Bélisle

  4. Université Laval, Quebec, QC, Canada

    Sehl Mellouli

  5. International University of Beirut, Mazraa, Lebanon

    Farid Abdallah

  6. American University of Beirut, Beirut, Lebanon

    Ibrahim Osman

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Mbazaia, O., Kamoun, K. (2019). CaRT: Framework for Semantic Query Correction and Relaxation. In: Jallouli, R., Bach Tobji, M., Bélisle, D., Mellouli, S., Abdallah, F., Osman, I. (eds) Digital Economy. Emerging Technologies and Business Innovation. ICDEc 2019. Lecture Notes in Business Information Processing, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-030-30874-2_12

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  • DOI: https://doi.org/10.1007/978-3-030-30874-2_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30873-5

  • Online ISBN: 978-3-030-30874-2

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