2016
DOI: 10.7249/rr1200
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Uncertainty-Sensitive Heterogeneous Information Fusion: Assessing Threat with Soft, Uncertain, and Conflicting Evidence

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Cited by 5 publications
(7 citation statements)
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“…analy sis needs to consider uncertainties in the model itself-i.e., structural uncertainties (Davis et al, 2016)-not just the pa ram e ter values of a given model.…”
Section: Rethinking Model Validity the Five Dimensions Of Model Validitymentioning
confidence: 99%
See 1 more Smart Citation
“…analy sis needs to consider uncertainties in the model itself-i.e., structural uncertainties (Davis et al, 2016)-not just the pa ram e ter values of a given model.…”
Section: Rethinking Model Validity the Five Dimensions Of Model Validitymentioning
confidence: 99%
“…This poses additional prob lems for modeling platforms if they are to support uncertainty analy sis broadly. Dealing with model uncertainty is a long-standing prob lem, but much can be done, as illustrated in recent work on heterogeneous information fusion (Davis et al, 2016).…”
Section: Implications For Analy Sis Outputs and Communicationmentioning
confidence: 99%
“…In our work we have frequently found it useful to separate discussion of snapshot causality and system dynamics (including feedbacks), to suppress some cross-linkages that are relatively weak, and to define variables of a tree left to right so that the higher level factors can be treated as logically independent. 29 Reality is complex; tricks are required to glimpse various aspects in seemingly simple ways.…”
Section: Qualitative Factor Trees As Thinking Modelsmentioning
confidence: 99%
“…This basic research study investigated ways to fuse heterogeneous information as part of detecting terrorists. 29,51 It sought to combine information types ranging from digital records on an individual’s background (e.g., prior arrests and convictions, travel history, weapons purchases), human sources (e.g., informants), and behavioral observations (e.g., deceptive behavior in an airport line). The information could be fragmentary, ambiguous, contradictory, or even deceptive.…”
Section: Using An Uncertain Social Science Model As Part Of Heterogmentioning
confidence: 99%
“…In that study we attempted to confront all the uncertainties of the problem, structural, parametric, and procedural. For example, we built in the ability to easily vary the functional forms for how factors combine, the values of related parameters, and even the order of processing reports (Davis et al, 2016). The same methods would apply for cognitive modeling.…”
Section: Extending Uncertainty Analysis In Simple Computational Sociamentioning
confidence: 99%