Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A survey of interestingness measures for knowledge discovery
The Knowledge Engineering Review
Interestingness measures for data mining: A survey
ACM Computing Surveys (CSUR)
A systematic approach to the assessment of fuzzy association rules
Data Mining and Knowledge Discovery
Elicitation of fuzzy association rules from positive and negative examples
Fuzzy Sets and Systems
Examples, counterexamples, and measuring fuzzy associations
Fuzzy Sets and Systems
A note on quality measures for fuzzy association rules
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Fuzzy association rules: general model and applications
IEEE Transactions on Fuzzy Systems
On the representation, measurement, and discovery of fuzzy associations
IEEE Transactions on Fuzzy Systems
Dependencies among attributes given by fuzzy confirmation measures
Expert Systems with Applications: An International Journal
Confirmation measures of association rule interestingness
Knowledge-Based Systems
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This paper proposes a number of measures for assessing the quality of fuzzy association rules. The focus is on a particular class of measures which are fuzzy counterparts of probabilistic confirmation measures. The distinguishing feature of such measures is that they are based on probabilistic (in)dependence and so a corresponding definition of fuzzy (in)dependence is proposed. This forms the basis for the definition of a fuzzy confirmation measure and for proposing a number of such measures based on a well-known fuzzy confidence measure. Various properties are considered to narrow the field of viable fuzzy confirmation measures, with one particular measure being found to have a number of advantages.