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Proceedings Paper

A survey of automated methods for sensemaking support
Author(s): James Llinas
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Paper Abstract

Complex, dynamic problems in general present a challenge for the design of analysis support systems and tools largely because there is limited reliable a priori procedural knowledge descriptive of the dynamic processes in the environment. Problem domains that are non-cooperative or adversarial impute added difficulties involving suboptimal observational data and/or data containing the effects of deception or covertness. The fundamental nature of analysis in these environments is based on composite approaches involving mining or foraging over the evidence, discovery and learning processes, and the synthesis of fragmented hypotheses; together, these can be labeled as sensemaking procedures. This paper reviews and analyzes the features, benefits, and limitations of a variety of automated techniques that offer possible support to sensemaking processes in these problem domains.

Paper Details

Date Published: 22 May 2014
PDF: 13 pages
Proc. SPIE 9122, Next-Generation Analyst II, 912206 (22 May 2014); doi: 10.1117/12.2053877
Show Author Affiliations
James Llinas, Univ. at Buffalo (United States)


Published in SPIE Proceedings Vol. 9122:
Next-Generation Analyst II
Barbara D. Broome; David L. Hall; James Llinas, Editor(s)

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