The Shapley Value of Inconsistency Measures for Functional Dependencies

Ester Livshits, Benny Kimelfeld

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Quantifying the inconsistency of a database is motivated by various goals including reliability estimation for new datasets and progress indication in data cleaning. Another goal is to attribute to individual tuples a level of responsibility to the overall inconsistency, and thereby prioritize tuples in the explanation or inspection of dirt. Therefore, inconsistency quantification and attribution have been a subject of much research in Knowledge Representation and, more recently, in Databases. As in many other fields, a conventional responsibility sharing mechanism is the Shapley value from cooperative game theory. In this paper, we carry out a systematic investigation of the complexity of the Shapley value in common inconsistency measures for functional-dependency (FD) violations. For several measures we establish a full classification of the FD sets into tractable and intractable classes with respect to Shapley-value computation. We also study the complexity of approximation in intractable cases
Original languageEnglish
Article number20
Number of pages33
JournalLogical Methods in Computer Science
Issue number2
Publication statusPublished - 15 Jun 2022

Keywords / Materials (for Non-textual outputs)

  • Shapley value
  • inconsistent databases
  • functional dependencies
  • database repairs


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