Visualization of directed associations in e-commerce transaction data

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dc.contributor.authorHao, Ming C.en_US
dc.contributor.authorDayal, Umeshwaren_US
dc.contributor.authorHsu, Meichunen_US
dc.contributor.authorSprenger, Thomasen_US
dc.contributor.authorGross, Markus H.en_US
dc.contributor.editorDavid S. Ebert and Jean M. Favre and Ronald Peikerten_US
dc.date.accessioned2014-01-30T06:45:57Z
dc.date.available2014-01-30T06:45:57Z
dc.date.issued2001en_US
dc.description.abstractMany 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.en_US
dc.description.seriesinformationEurographics / IEEE VGTC Symposium on Visualizationen_US
dc.identifier.isbn3-211-83674-8en_US
dc.identifier.issn1727-5296en_US
dc.identifier.urihttps://doi.org/10.2312/VisSym/VisSym01/185-192en_US
dc.publisherThe Eurographics Associationen_US
dc.titleVisualization of directed associations in e-commerce transaction dataen_US
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