FpViz: a visualizer for frequent pattern mining

  • Authors:
  • Carson Kai-Sang Leung;Christopher L. Carmichael

  • Affiliations:
  • The University of Manitoba, Winnipeg, MB, Canada;The University of Manitoba, Winnipeg, MB, Canada

  • Venue:
  • Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration
  • Year:
  • 2009

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Abstract

Over the past 15 years, numerous algorithms have been proposed for frequent pattern mining as it plays an essential role in many knowledge discovery and data mining (KDD) tasks. Most of these frequent pattern mining algorithms return the mined results in the form of textual lists containing frequent patterns showing those frequently occurring sets of items. It is well known that "a picture is worth a thousand words". The use of visual representation can enhance the user understanding of the inherent relations in a collection of frequent patterns. A few visualizers have been developed to visualize the input data or the mined results. However, most of these visualizers were not designed for visualizing the mined frequent patterns. In this paper, we develop a visualizer for frequent pattern mining. Such a visualizer---called FpViz---gives users an insight about the data, allows them to zoom in and zoom out, and provides details on demand. Moreover, FpViz is also equipped with several interactive features for effective visual support in the data analysis and KDD process for various real-life applications.