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Plethoric Answers to Fuzzy Queries: A Reduction Method Based on Query Mining

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Foundations of Intelligent Systems (ISMIS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8502))

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Abstract

Querying large-scale databases may often lead to plethoric answers, even when fuzzy queries are used. To overcome this problem, we propose to strengthen the initial query with additional predicates, selected among predefined ones according mainly to their degree of semantic relationship with the initial query. In the approach we propose, related predicates are identified by mining a repository of previously executed queries.

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Author information

Authors and Affiliations

  1. University of Rennes 1, Irisa, Lannion, France

    Olivier Pivert & Grégory Smits

Authors
  1. Olivier Pivert
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  2. Grégory Smits
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Editor information

Editors and Affiliations

  1. Research Group PLIS: Programming, Logic and Intelligent Systems Dept. of Communication, Business and Information Technologies, Roskilde University, Denmark

    Troels Andreasen  & Henning Christiansen  & 

  2. Department of Computer Science and Artificial Intelligence, CITIC, University of Granada, 18071, Granada, Spain

    Juan-Carlos Cubero

  3. University of North Carolina, , , 9201 University City Blvd, Charlotte, NC 28223 USA, and Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665 Warsaw, Poland

    Zbigniew W. Raś

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Pivert, O., Smits, G. (2014). Plethoric Answers to Fuzzy Queries: A Reduction Method Based on Query Mining. In: Andreasen, T., Christiansen, H., Cubero, JC., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2014. Lecture Notes in Computer Science(), vol 8502. Springer, Cham. https://doi.org/10.1007/978-3-319-08326-1_30

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  • DOI: https://doi.org/10.1007/978-3-319-08326-1_30

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08325-4

  • Online ISBN: 978-3-319-08326-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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