Paper
22 May 2014 A survey of automated methods for sensemaking support
Author Affiliations +
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.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James Llinas "A survey of automated methods for sensemaking support", Proc. SPIE 9122, Next-Generation Analyst II, 912206 (22 May 2014); https://doi.org/10.1117/12.2053877
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Visualization

Analytical research

Information fusion

Visual analytics

Data fusion

Data modeling

Data acquisition

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