Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Fast discovery of association rules
Advances in knowledge discovery and data mining
Web for data mining: organizing and interpreting the discovered rules using the Web
ACM SIGKDD Explorations Newsletter
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A survey of Knowledge Discovery and Data Mining process models
The Knowledge Engineering Review
A Methodology for Exploring Association Models
Visual Data Mining
Artificial Intelligence Review
A tool for interactive subgroup discovery using distribution rules
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Meta-learning for post-processing of association rules
DaWaK'10 Proceedings of the 12th international conference on Data warehousing and knowledge discovery
Visual interactive subgroup discovery with numerical properties of interest
DS'06 Proceedings of the 9th international conference on Discovery Science
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Association rule engines typically output a very large set of rules. Despite the fact that association rules are regarded as highly comprehensible and useful for data mining and decision support in fields such as marketing, retail, demographics, among others, lengthy outputs may discourage users from using the technique. In this paper we propose a post-processing methodology and tool for browsing/visualizing large sets of association rules. The method is based on a set of operators that transform sets of rules into sets of rules, allowing focusing on interesting regions of the rule space. Each set of rules can be then seen with different graphical representations. The tool is web-based and uses SVG. Association rules are given in PMML