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Data-Quality-Aware Skyline Queries

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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

This paper deals with skyline queries in the context of “dirty databases”, i.e., databases that may contain bad quality or suspect data. We assume that each tuple or attribute value of a given dataset is associated with a quality level and we define several extensions of skyline queries that make it possible to take data quality into account when checking whether a tuple is dominated by another. This leads to the computation of different types of gradual (fuzzy) skylines.

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Author information

Authors and Affiliations

  1. Université de Rennes 1, Irisa, Lannion, France

    Hélène Jaudoin, Olivier Pivert, Grégory Smits & Virginie Thion

Authors
  1. Hélène Jaudoin
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  2. Olivier Pivert
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  3. Grégory Smits
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  4. Virginie Thion
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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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© 2014 Springer International Publishing Switzerland

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Jaudoin, H., Pivert, O., Smits, G., Thion, V. (2014). Data-Quality-Aware Skyline Queries. 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_56

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  • DOI: https://doi.org/10.1007/978-3-319-08326-1_56

  • 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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