The Shapley Value of Inconsistency Measures for Functional Dependencies

• Published in: Logical methods in computer science Vol. 18, Issue 2
• Main Authors: Livshits, Ester, Kimelfeld, Benny
• Format: Journal Article
• Language: English
• Published: Logical Methods in Computer Science e.V 15.06.2022
• Subjects: computer science - databases
• ISSN: 1860-5974; 1860-5974
• DOI: 10.46298/lmcs-18(2:20)2022

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.