Augmented Visualization of Association Rules for Data Mining

In this paper, the authors describe a proposal for enhanced visualization of a data mining model generated with Association Rule (AR) techniques by applying Self Organizing Maps (SOMs). A representation of visual perception model of AR based on a method called AVM-DM (Augmented Visualization Models for Data Mining) is established, together with data and patterns, which support the visual exploration stage, thus fitting in the context of the KDD (Knowledge Discovery in Database) process. This methodology seeks to answer generic user questions regarding the inner workings of the model, and to support understanding the generated model.

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RWTH Aachen University
Data Management