FpViz: a visualizer for frequent pattern mining
Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration
Mining uncertain data for constrained frequent sets
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
SMARViz: Soft Maximal Association Rules Visualization
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
FpVAT: a visual analytic tool for supporting frequent pattern mining
ACM SIGKDD Explorations Newsletter
CloseViz: visualizing useful patterns
Proceedings of the ACM SIGKDD Workshop on Useful Patterns
Visual analytics of social networks: mining and visualizing co-authorship networks
FAC'11 Proceedings of the 6th international conference on Foundations of augmented cognition: directing the future of adaptive systems
A clustering-based visualization of colocation patterns
Proceedings of the 15th Symposium on International Database Engineering & Applications
RadialViz: an orientation-free frequent pattern visualizer
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
WLAR-Viz: weighted least association rules visualization
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
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Frequent itemset mining plays an essential role in the mining of many different patterns. Most existing frequent itemset mining algorithms return the mined results--namely, frequent itemsets--in the form of textual lists. However, the use of visual representation can enhance the user understanding of the inherent relations in a collection of frequent itemsets. In this paper, we propose an effective visualizer, called WiFIsViz, to display the mined frequent itemsets. WiFIsViz provides users with an overview and details about the itemsets. Moreover, this visualizer is also equipped with several interactive features for effective visualization of the frequent itemsets mined from various real-life applications.