Soft information, dirty graphs and uncertainty representation/processing for situation understanding

Geoff Gross, Rakesh Nagi, Kedar Sambhoos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In conventional warfare as well as counter-insurgency (COIN) operations, the understanding of the situation is extremely vital to assure a sense of security. Intelligence in COIN is about people, and deployed units in the field are the best sources of intelligence. Past and present intelligence data is analyzed to look for changes in the insurgents' approach or tactics. To do this, graphical methods have proven to be effective. In recent work, [10], have developed an inexact subgraph matching algorithm as a variation of the subgraph isomorphism approach for situation assessment. This paper enhances this procedure to represent inaccurate observations or data estimates, and inaccurate structural representations of a state of interest, thus accounting for the uncertainties. Various probabilistic and possibilistic uncertainty representations, transformations between representations and methods for establishing similarities between representations have been reviewed. This comprehensible approach will give pragmatic estimates providing rigor and sound understanding during situation assessment.

Original languageEnglish (US)
Title of host publication13th Conference on Information Fusion, Fusion 2010
StatePublished - Dec 1 2010
Externally publishedYes
Event13th Conference on Information Fusion, Fusion 2010 - Edinburgh, United Kingdom
Duration: Jul 26 2010Jul 29 2010

Publication series

Name13th Conference on Information Fusion, Fusion 2010

Other

Other13th Conference on Information Fusion, Fusion 2010
Country/TerritoryUnited Kingdom
CityEdinburgh
Period7/26/107/29/10

Keywords

  • Inexact graph matching
  • Situation assessment
  • Uncertainty representation

ASJC Scopus subject areas

  • Information Systems

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