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Measuring and Comparing Effectiveness of Data Quality Techniques

  • Lei Jiang
  • Daniele Barone
  • Alex Borgida
  • John Mylopoulos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5565)

Abstract

Poor quality data may be detected and corrected by performing various quality assurance activities that rely on techniques with different efficacy and cost. In this paper, we propose a quantitative approach for measuring and comparing the effectiveness of these data quality (DQ) techniques. Our definitions of effectiveness are inspired by measures proposed in Information Retrieval. We show how the effectiveness of a DQ technique can be mathematically estimated in general cases, using formal techniques that are based on probabilistic assumptions. We then show how the resulting effectiveness formulas can be used to evaluate, compare and make choices involving DQ techniques.

Keywords

data quality technique data quality measure data quality assurance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Lei Jiang
    • 1
  • Daniele Barone
    • 2
  • Alex Borgida
    • 1
    • 3
  • John Mylopoulos
    • 1
    • 4
  1. 1.Dept. of Computer ScienceUniversity of TorontoCanada
  2. 2.Dept. of Computer ScienceUniversità di Milano BicoccaItaly
  3. 3.Dept. of Computer ScienceRutgers UniversityUSA
  4. 4.Dept. of Information Engineering and Computer ScienceUniversity of TrentoItaly

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