2011 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2011
DOI: 10.1109/cogsima.2011.5753441
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Augmenting the analyst via situation-dependent reasoning with trust-annotated facts

Abstract: We say that a computer program augments the analyst if it can infer facts that are implicit in existing information, but that may be relatively difficult for a human to infer. Among a multitude of reasons, the analyst's task is difficult because (1) reported information to be analyzed and reasoned about often cannot be completely trusted (requiring verification attempts via further collection of information, corroboration where verification is not possible, and/or assumption-based reasoning) and (2) evaluation… Show more

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Cited by 4 publications
(2 citation statements)
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“…Since the goal is to capture situations, we use the Situation Theory Ontology (STO) 7 with certain extensions. 8 Figure 4 presents the main concepts of this ontology. The central class of this ontology is Situation.…”
Section: Situation Representationmentioning
confidence: 99%
“…Since the goal is to capture situations, we use the Situation Theory Ontology (STO) 7 with certain extensions. 8 Figure 4 presents the main concepts of this ontology. The central class of this ontology is Situation.…”
Section: Situation Representationmentioning
confidence: 99%
“…To facilitate research in MOVINT, the Columbus Large Image Format (CLIF) Data was collected by deploying a distributed set of sensors to monitor, track, and classify vehicles [80] which includes a list of challenge problems such as joint data management (JDM) for data-to-decisions (D2D) [81]. In this example, we use the results collected and analyzed over the CLIF data to analyze a DSS for an Image Analyst.…”
Section: Example Of Decision Support For Image Analyst Functionsmentioning
confidence: 99%