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A Framework for Analyst Focus from Computed Significance

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Counterterrorism and Open Source Intelligence

Part of the book series: Lecture Notes in Social Networks ((LNSN))

Abstract

Attention is the critical resource for intelligence analysts, so tools that provide focus are useful. One way to determine focus is by computing significance. In the context of a known model, new data can be placed on a spectrum defined by: normal, anomalous, interesting, novel, or random; and significance is greatest towards the middle of this spectrum. However, significance also depends on the mental state of the analyst (and the organization). A framework for understanding significance is defined, and its impact on the knowledge–discovery process is explored.

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Notes

  1. 1.

    This is the random walk Laplacian.

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Author information

Authors and Affiliations

  1. School of Computing, Queen’s University, Kingston, ON, Canada

    David Skillicorn

  2. Royal Military College of Canada, Kingston, Ontario, Canada

    M. A. J. Bourassa

Authors
  1. David Skillicorn
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  2. M. A. J. Bourassa
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Correspondence to David Skillicorn .

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Editors and Affiliations

  1. The Maersk McKinney Moller Institute, University of Southern Denmark, Campusvej 55, 5230, Odense, Denmark

    Uffe Kock Wiil

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Skillicorn, D., Bourassa, M.A.J. (2011). A Framework for Analyst Focus from Computed Significance. In: Wiil, U.K. (eds) Counterterrorism and Open Source Intelligence. Lecture Notes in Social Networks. Springer, Vienna. https://doi.org/10.1007/978-3-7091-0388-3_3

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  • DOI: https://doi.org/10.1007/978-3-7091-0388-3_3

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  • Online ISBN: 978-3-7091-0388-3

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