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Proceedings Paper

Improving data signature construction through vector fusion quantitative analysis
Author(s): Jasmine A. Malinao; Richelle Ann B. Juayong; Henry N. Adorna
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Paper Abstract

In this paper, a new set of data signatures is derived to obtain better Vector Fusion 2D visualizations of a time series and periodic nD traffic data set as compared with previous work. The latter had used the entire Power Spectrum components representative of each subset of the time domain data for visualization purposes. As problems arise in interpreting the latter set of visualizations, we propose in this paper optimal constructions of data signatures to eliminate such problems. An improved set of qualitative criterion is drawn to measure the goodness of the 2D data signature-based visual representation of the original nD data set. To support the results from using this criteria, we formulate an algorithm to quantify this measure and conclude an appropriate construction of data signatures for the data set. Finally, we provide empirical testing and discuss the results.

Paper Details

Date Published:
PDF: 6 pages
Proc. SPIE 7868, Visualization and Data Analysis 2011, 78680S; doi: 10.1117/12.872293
Show Author Affiliations
Jasmine A. Malinao, Univ. of the Philippines (Philippines)
Richelle Ann B. Juayong, Univ. of the Philippines (Philippines)
Henry N. Adorna, Univ. of the Philippines (Philippines)

Published in SPIE Proceedings Vol. 7868:
Visualization and Data Analysis 2011
Pak Chung Wong; Jinah Park; Ming C. Hao; Chaomei Chen; Katy Börner; David L. Kao; Jonathan C. Roberts, Editor(s)

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