Visualization of directed associations in e-commerce transaction data

  • Ming C. Hao
  • Umeshwar Dayal
  • Meichun Hsu
  • Thomas Sprenger
  • Markus H. Gross
Part of the Eurographics book series (EUROGRAPH)


Many real-world e-commerce applications require the mining of large volumes of transaction data to extract marketing and sales information. This paper describes the Directed Association Visualization (DAV) system that visually associates product affinities and relationships for large volumes of e-commerce transaction data. DAV maps transaction data items and their relationships to vertices, edges, and positions on a visual spherical surface. DAV encompasses several innovative techniques (1) items are positioned according to their associations to show the strength of their relationships; (2) edges with arrows are used to represent the implication directions; (3) a mass-spring engine is integrated into a visual data mining platform to provide a self-organized graph. We have applied this system successfully to market basket analysis and e-customer profiling Internet applications.


Association Rule Purchasing Behavior Related Item Transaction Data Information Visualization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • Ming C. Hao
    • 1
  • Umeshwar Dayal
    • 1
  • Meichun Hsu
    • 1
  • Thomas Sprenger
    • 2
  • Markus H. Gross
    • 2
  1. 1.Hewlett Packard Research LaboratoriesPalo AltoUSA
  2. 2.Department of Computer ScienceSwiss Federal Institute Of TechnologyZurichSwitzerland

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