Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Visualizing Association Rules for Text Mining
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
Inventing discovery tools: combining information visualization with data mining
Information Visualization
Analyzing multi-level spatial association rules through a graph-based visualization
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Research issues in data stream association rule mining
ACM SIGMOD Record
Visual Mining of Association Rules
Visual Data Mining
SMARViz: Soft Maximal Association Rules Visualization
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
Proceedings of the 39th annual ACM SIGUCCS conference on User services
Visualizing association rules in a framework for visual data mining
From Integrated Publication and Information Systems to Virtual Information and Knowledge Environments
WLAR-Viz: weighted least association rules visualization
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
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The abundance of data available nowadays fosters the need of developing tools and methodologies to help users in extracting significant information. Visual data mining is going in this direction, exploiting data mining algorithms and methodologies together with information visualization techniques.The demand for visual and interactive analysis tools is particularly pressing in the Association Rules context where often the user has to analyze hundreds of rules in order to grasp valuable knowledge. This paper presents a visual strategy to face this drawback by exploiting graph-based technique and parallel coordinates to visualize the results of association rules mining algorithms. The combination of the two approaches allows both to get an overview on the association structure hidden in the data and to deeper investigate inside a specific set of rules selected by the user.