The mathematics of inheritance systems
The mathematics of inheritance systems
A Reasoning Model Based on the Production of Acceptable Arguments
Annals of Mathematics and Artificial Intelligence
A cost-based model and effective heuristic for repairing constraints by value modification
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Measuring inconsistency in knowledgebases
Journal of Intelligent Information Systems
Using similarity-based operations for resolving data-level conflicts
BNCOD'03 Proceedings of the 20th British national conference on Databases
Consistent query answering: five easy pieces
ICDT'07 Proceedings of the 11th international conference on Database Theory
Approaches to measuring inconsistent information
Inconsistency Tolerance
Analysing inconsistent first-order knowledgebases
Artificial Intelligence
A three-valued semantics for querying and repairing inconsistent databases
Annals of Mathematics and Artificial Intelligence
Handling dirty databases: from user warning to data cleaning -- towards an interactive approach
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
Detecting suspect answers in the presence of inconsistent information
FoIKS'12 Proceedings of the 7th international conference on Foundations of Information and Knowledge Systems
Inconsistency-Induced Learning for Perpetual Learners
International Journal of Software Science and Computational Intelligence
Measuring inconsistency through minimal proofs
ECSQARU'13 Proceedings of the 12th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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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.