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Detecting patterns of change using enhanced parallel coordinates visualization

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4 Author(s)
K. Zhao ; Dept. of Comput. Sci., Illinois Univ., Chicago, IL, USA ; B. Liu ; T. M. Tirpak ; A. Schaller

Analyzing data to find trends, correlations, and stable patterns is an important problem for many industrial applications. We propose a new technique based on parallel coordinates visualization. Previous work on parallel coordinates method has shown that they are effective only when variables that are correlated and/or show similar patterns are displayed adjacently. Although current parallel coordinates tools allow the user to manually rearrange the order of variables, this process is very time-consuming when the number of variables is large. Automated assistance is needed. We propose an edit-distance based technique to rearrange variables so that interesting patterns can be easily detected. Our system, V-Miner, includes both automated methods for visualizing common patterns and a query tool that enables the user to describe specific target patterns to be mined/displayed by the system. Following an overview of the system, a case study is presented to explain how Motorola engineers have used V-Miner to identify significant patterns in their product test and design data.

Published in:

Data Mining, 2003. ICDM 2003. Third IEEE International Conference on

Date of Conference:

19-22 Nov. 2003