A database perspective on knowledge discovery
Communications of the ACM
The process of knowledge discovery in databases
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Multi-level organization and summarization of the discovered rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
MSQL: A Query Language for Database Mining
Data Mining and Knowledge Discovery
Improving the Discovery of Association Rules with Intensity of Implication
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
A User-Driven Process for Mining Association Rules
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining 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
DBMiner: a system for data mining in relational databases and data warehouses
CASCON '97 Proceedings of the 1997 conference of the Centre for Advanced Studies on Collaborative research
Visualizing Association Rules for Text Mining
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
Visual Analytics: A 2D-3D visualization support for human-centered rule mining
Computers and Graphics
A Unified View of Objective Interestingness Measures
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Exploration of SWRL Rule Bases through Visualization, Paraphrasing, and Categorization of Rules
RuleML '09 Proceedings of the 2009 International Symposium on Rule Interchange and Applications
Contingency structures and concept analysis
ICFCA'08 Proceedings of the 6th international conference on Formal concept analysis
Utilisation d'outils de visual data mining pour l'exploration d'un ensemble de règles d'association
23rd French Speaking Conference on Human-Computer Interaction
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On account of the enormous amounts of rules that canbe produced by data mining algorithms, knowledgevalidation is one of the most problematic steps in anassociation rule discovery process.In order to findrelevant knowledge for decision-making, the user needs toreally rummage through the rules.Visualization can bevery beneficial to support him/her in this task byimproving the intelligibility of the large rule sets andenabling the user to navigate inside them.In this article,we propose to answer the association rule validationproblem by designing a human-centered visualizationmethod for the rule rummaging task.This new approachbased on a specific rummaging model relies on ruleinterestingness measures and on interactive rule subsetfocusing and mining.We have implemented ourrepresentation by developing a first experimentalprototype called ARVis.