Semantics and consistency of empirical databases
ICLP'93 Proceedings of the tenth international conference on logic programming on Logic programming
Efficient mining of association rules using closed itemset lattices
Information Systems
Linear Programming in Linear Time When the Dimension Is Fixed
Journal of the ACM (JACM)
Fuzzy linguistic summaries via association rules
Data mining and computational intelligence
Mining for Strong Negative Associations in a Large Database of Customer Transactions
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Concise Representation of Frequent Patterns Based on Generalized Disjunction-Free Generators
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Efficient mining of both positive and negative association rules
ACM Transactions on Information Systems (TOIS)
Mining Non-Redundant Association Rules
Data Mining and Knowledge Discovery
Generating a Condensed Representation for Association Rules
Journal of Intelligent Information Systems
Mining positive and negative association rules: an approach for confined rules
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Computational complexity of itemset frequency satisfiability
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Minimum-Size Bases of Association Rules
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Deduction Schemes for Association Rules
DS '08 Proceedings of the 11th International Conference on Discovery Science
Theory and Practice of Logic Programming
RDF semantics for web association rules
RR'11 Proceedings of the 5th international conference on Web reasoning and rule systems
Efficient mining of dissociation rules
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Essential patterns: a perfect cover of frequent patterns
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
A survey on condensed representations for frequent sets
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
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The support and confidence of association rules are defined in terms of itemset frequencies. While deciding the satisfiability of a set of itemset frequencies is known to be an NPTIME complete problem when frequencies are specified through rational ranges, this complexity result is too wide. To achieve tractability, two simpler problems are studied, instead. Both receive a set of association rules as input, each rule provided with exact support and confidence values, and the decision is to be made, respectively on the consistency of the addition and on the implication of a goal rule. Both allow bounds for the support and confidence values of the goal to be specified, and only admit itemsets relevant to the rules to have non-empty extensions in a model. We show that the problems are tractable and efficient algorithms for them are presented.