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
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Applied numerical linear algebra
Applied numerical linear algebra
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
A statistical theory for quantitative association rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient discovery of error-tolerant frequent itemsets in high dimensions
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering associations with numeric variables
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Bump hunting in high-dimensional data
Statistics and Computing
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A Theoretical Framework for Association Mining Based on the Boolean Retrieval Model
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Generalizing the notion of support
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Mining multi-dimensional quantitative associations
INAP'01 Proceedings of the Applications of prolog 14th international conference on Web knowledge management and decision support
Generalizing the notion of confidence
Knowledge and Information Systems
Association rules induced by item and quantity purchased
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
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In this paper, we explore extending association analysis to non-traditional types of patterns and non-binary data by generalizing the notion of confidence. The key idea is to regard confidence as a measure of the extent to which the strength of one association pattern provides information about the strength of another. This approach provides a framework that encompasses the traditional concept of confidence as a special case and can be used as the basis for designing a variety of new confidence measures. Besides discussing such confidence measures, we provide examples that illustrate the potential usefulness of a generalized notion of confidence. In particular, we describe an approach to defining confidence for error tolerant itemsets that preserves the interpretation of confidence as a conditional probability and derive a confidence measure for continuous data that agrees with the standard confidence measure when applied to binary transaction data.