Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
An XML-based agent model for supporting user activities on the Web
Web Intelligence and Agent Systems
Artificial immune system for associative classification
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Mining class association rules with artificial immune system
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
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Association rules are "if-then rules" with two measures which quantify the support and confidence of the rule for a given data set. Having their origin in market basked analysis, association rules are now one of the most popular tools in data mining. This popularity is to a large part due to the availability of efficient algorithms following from the development of the Apriori algorithm.We will review the basic Apriori algorithm and discuss variants for distributed data, inclusion of constraints and data taxonomies. The review ends with an outlook on tools which have the potential to deal with long itemsets and considerably reduce the amount of (uninteresting) itemsets returned. The discussion will focus on the problem of finding frequent itemsets.