How dirty is your relational database? An axiomatic approach

Maria Vanina Martinez*, Andrea Pugliese, Gerardo I. Simari, V. S. Subrahmanian, Henri Prade

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

41 Scopus citations

Abstract

There has been a significant amount of interest in recent years on how to reason about inconsistent knowledge bases. However, with the exception of three papers by Lozinskii, Hunter and Konieczny and by Grant and Hunter, there has been almost no work on characterizing the degree of dirtiness of a database. One can conceive of many reasonable ways of characterizing how dirty a database is. Rather than choose one of many possible measures, we present a set of axioms that any dirtiness measure must satisfy. We then present several plausible candidate dirtiness measures from the literature (including those of Hunter-Konieczny and Grant-Hunter) and identify which of these satisfy our axioms and which do not. Moreover, we define a new dirtiness measure which satisfies all of our axioms.

Original languageEnglish (US)
Title of host publicationSymbolic and Quantitative Approaches to Reasoning with Uncertainty - 9th European Conference, ECSQARU 2007, Proceedings
PublisherSpringer Verlag
Pages103-114
Number of pages12
ISBN (Print)9783540752554
DOIs
StatePublished - 2007
Externally publishedYes
Event9th European Conference on Symbolic and Qualitative Approaches to Reasoning with Uncertainty, ECSQARU 2007 - Hammamet, Tunisia
Duration: Oct 31 2007Nov 2 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4724 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th European Conference on Symbolic and Qualitative Approaches to Reasoning with Uncertainty, ECSQARU 2007
Country/TerritoryTunisia
CityHammamet
Period10/31/0711/2/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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