Fast discovery of association rules
Advances in knowledge discovery and data mining
Visual classification: an interactive approach to decision tree construction
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Visualizing association rules with interactive mosaic plots
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Visualization Techniques for Mining Large Databases: A Comparison
IEEE Transactions on Knowledge and Data Engineering
Query, analysis, and visualization of hierarchically structured data using Polaris
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
INFOVIS '00 Proceedings of the IEEE Symposium on Information Vizualization 2000
Visualizing Sequential Patterns for Text Mining
INFOVIS '00 Proceedings of the IEEE Symposium on Information Vizualization 2000
A two-way visualization method for clustered data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Pruning and Visualizing Generalized Association Rules in Parallel Coordinates
IEEE Transactions on Knowledge and Data Engineering
Interactive visual exploration of association rules with rule-focusing methodology
Knowledge and Information Systems
WiFIsViz: Effective Visualization of Frequent Itemsets
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Lark: Coordinating Co-located Collaboration with Information Visualization
IEEE Transactions on Visualization and Computer Graphics
Visualizing frequent itemsets, association rules, and sequential patterns in parallel coordinates
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
FIsViz: a frequent itemset visualizer
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
FpVAT: a visual analytic tool for supporting frequent pattern mining
ACM SIGKDD Explorations Newsletter
OA-graphs: orientation agnostic graphs for improving the legibility of charts on horizontal displays
ACM International Conference on Interactive Tabletops and Surfaces
Visually Contrast Two Collections of Frequent Patterns
ICDMW '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining Workshops
FpMapViz: A Space-Filling Visualization for Frequent Patterns
ICDMW '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining Workshops
Analyzing the role of dimension arrangement for data visualization in radviz
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
A novel scalable multi-class ROC for effective visualization and computation
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
A constrained frequent pattern mining system for handling aggregate constraints
Proceedings of the 16th International Database Engineering & Applications Sysmposium
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Frequent pattern mining algorithms aim to find sets of frequently co-occurring items. Visual representation of the mining results is more comprehensible to users than the traditional long textual list of frequent patterns. Existing visualizers mostly show frequent patterns as graphs in a two-dimensional space with (x ,y )-coordinates. Nowadays, in a collaborative environment, it is not uncommon for users to have face-to-face meetings when they show the graphs visualizing frequent patterns. In these situations, the viewing orientation of the graphs plays an important role as different orientations positively or negatively impact the graph legibility. A legible right-side-up graph to one user may become an illegible upside-down graph towards another user. In this paper, we propose a visualizer that uses a radial layout--which is orientation free--to show frequent patterns. Having such a visualizer is beneficial in the collaborative environment.