Abstract
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. In this paper, we present a visual strategy that exploits a graph-based technique and parallel coordinates to visualize the results of association rule mining algorithms. This helps data miners to get an overview of the rule set they are interacting with and enables them to deeper investigate inside a specific set of rules. The tools developed are embedded in a framework for Visual Data Mining that is briefly described.
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Buono, P., Costabile, M.F. (2005). Visualizing Association Rules in a Framework for Visual Data Mining. In: Hemmje, M., Niederée, C., Risse, T. (eds) From Integrated Publication and Information Systems to Information and Knowledge Environments. Lecture Notes in Computer Science, vol 3379. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31842-2_22
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DOI: https://doi.org/10.1007/978-3-540-31842-2_22
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