Data-Quality-Aware Skyline Queries

  • Hélène Jaudoin
  • Olivier Pivert
  • Grégory Smits
  • Virginie Thion
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8502)


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.


Data Quality Membership Degree Skyline Query Possibility Theory Quality Degree 
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 2014

Authors and Affiliations

  • Hélène Jaudoin
    • 1
  • Olivier Pivert
    • 1
  • Grégory Smits
    • 1
  • Virginie Thion
    • 1
  1. 1.Université de Rennes 1IrisaFrance

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