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Proceedings Paper

Guided text analysis using adaptive visual analytics
Author(s): Chad A. Steed; Christopher T. Symons; Frank A. DeNap; Thomas E. Potok
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Paper Abstract

This paper demonstrates the promise of augmenting interactive visualizations with semi-supervised machine learning techniques to improve the discovery of significant associations and insight in the search and analysis of textual information. More specifically, we have developed a system-called Gryffin-that hosts a unique collection of techniques that facilitate individualized investigative search pertaining to an ever-changing set of analytical questions over an indexed collection of open-source publications related to national infrastructure. The Gryffin client hosts dynamic displays of the search results via focus+context record listings, temporal timelines, term-frequency views, and multiple coordinated views. Furthermore, as the analyst interacts with the display, the interactions are recorded and used to label the search records. These labeled records are then used to drive semi-supervised machine learning algorithms that re-rank the unlabeled search records such that potentially relevant records are moved to the top of the record listing. Gryffin is described in the context of the daily tasks encountered at the Department of Homeland Security's Fusion Centers, with whom we are collaborating in its development. The resulting system is capable of addressing the analysts information overload that can be directly attributed to the deluge of information that must be addressed in search and investigative analysis of textual information.

Paper Details

Date Published: 24 January 2012
PDF: 14 pages
Proc. SPIE 8294, Visualization and Data Analysis 2012, 829408 (24 January 2012); doi: 10.1117/12.904904
Show Author Affiliations
Chad A. Steed, Oak Ridge National Lab. (United States)
Christopher T. Symons, Oak Ridge National Lab. (United States)
Frank A. DeNap, Oak Ridge National Lab. (United States)
Thomas E. Potok, Oak Ridge National Lab. (United States)

Published in SPIE Proceedings Vol. 8294:
Visualization and Data Analysis 2012
Pak Chung Wong; David L. Kao; Ming C. Hao; Chaomei Chen; Robert Kosara; Mark A. Livingston; Jinah Park; Ian Roberts, Editor(s)

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