A comparison of similarity measures of fuzzy values
Fuzzy Sets and Systems
A comparative study of similarity measures
Fuzzy Sets and Systems
Coherence measures on finite fuzzy sets
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - special issue on measures and aggregation: formal aspects and applications to clustering and decision
Two Information Measures for Inconsistent Sets
Journal of Logic, Language and Information
Coherence, Explanation, and Bayesian Networks
AICS '02 Proceedings of the 13th Irish International Conference on Artificial Intelligence and Cognitive Science
Measuring inconsistency in knowledge via quasi-classical models
Eighteenth national conference on Artificial intelligence
International Journal of Intelligent Systems
Making argumentation more believable
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Quantifying information and contradiction in propositional logic through test actions
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Measuring conflict and agreement between two prioritized belief bases
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Approaches to measuring inconsistent information
Inconsistency Tolerance
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Intuitively it seems that the coherence of information received from heterogeneous sources should be one factor in determining the reliability or truthfulness of the information, yet the concept of coherence is extremely difficult to define. This paper draws on recent work on probabilistic measures of coherence by investigating two measures with contrasting properties and then explores how this work relates to similarity of fuzzy sets and comparison of knowledge bases in cases where inconsistency is present. In each area contrasting measures are proposed analogous to the probabilistic case. In particular, concepts of fuzzy and logical independence are proposed and in each area it is found that sensitivity to the relevant concept of independence is a distinguishing feature between the contrasting measures. In the case of inconsistent knowledge bases, it is argued that it is important to take agreeing information and not just conflicting and total information into account when comparing two knowledge bases. One of the measures proposed achieves this and is shown to have a number of properties which enable it to overcome some problems encountered by other approaches.