Guided text analysis using adaptive visual analytics

Chad A. Steed, Christopher T. Symons, Frank A. DeNap, Thomas E. Potok

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2012
DOIs
StatePublished - 2012
EventVisualization and Data Analysis 2012 - Burlingame, CA, United States
Duration: Jan 23 2012Jan 25 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8294
ISSN (Print)0277-786X

Conference

ConferenceVisualization and Data Analysis 2012
Country/TerritoryUnited States
CityBurlingame, CA
Period01/23/1201/25/12

Keywords

  • Machine learning
  • Search interfaces
  • Text visualization
  • Visual analytics

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