Interactive Visual Analytics of Databases and Frequent Sets

Carson K.S. Leung, Christopher L. Carmichael, Patrick Johnstone and David Sonny Hung-Cheung Yuen
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Carson K.S. Leung: University of Manitoba, Winnipeg, Canada
Christopher L. Carmichael: University of Manitoba, Winnipeg, Canada
Patrick Johnstone: University of Manitoba, Winnipeg, Canada
David Sonny Hung-Cheung Yuen: University of Manitoba, Winnipeg, Canada

International Journal of Information Retrieval Research (IJIRR), 2013, vol. 3, issue 4, 120-140

Abstract: In numerous real-life applications, large databases can be easily generated. Implicitly embedded in these databases is previously unknown and potentially useful knowledge such as frequently occurring sets of items, merchandise, or events. Different algorithms have been proposed for managing and retrieving useful information from these databases. Various algorithms have also been proposed for mining these databases to find frequent sets, which are usually presented in a lengthy textual list. As “a picture is worth a thousand words”, the use of visual representations can enhance user understanding of the inherent relationships among the mined frequent sets. Many of the existing visualizers were not designed to visualize these mined frequent sets. In this journal article, an interactive visual analytic system is proposed for providing visual analytic solutions to the frequent set mining problem. The system enables the management, visualization, and advanced analysis of the original transaction databases as well as the frequent sets mined from these databases.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:3:y:2013:i:4:p:120-140

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