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The Shapley Value of Inconsistency Measures for Functional Dependencies
- Source :
- Logical Methods in Computer Science, Vol Volume 18, Issue 2 (2022)
- Publication Year :
- 2022
- Publisher :
- Logical Methods in Computer Science e.V., 2022.
-
Abstract
- 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.
Details
- Language :
- English
- ISSN :
- 18605974
- Volume :
- ume 18, Issue 2
- Database :
- Directory of Open Access Journals
- Journal :
- Logical Methods in Computer Science
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f86801d66b3241bebdaade750235f4c3
- Document Type :
- article
- Full Text :
- https://doi.org/10.46298/lmcs-18(2:20)2022