Using AI for Sensemaking in Investigative Analysis
نویسندگان
چکیده
The sensemaking task in investigative analysis generates models that connect entities and events in an input stream of data. We describe a knowledge system for aiding sensemaking in investigative analysis. The STAB system represents crime schemas as hierarchical scripts with goals and states. It generates multiple explanatory hypotheses for an input data stream containing interleaved sequences of events, recognizes intent in a specific event sequence, and calculates confidence values for the generated hypotheses. We view STAB as an automated cognitive assistant to human analysts: it may support sensemaking in investigative analysis by generating and managing multiple competing hypotheses.
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Playing Detective: Using AI for Sensemaking in Investigative Analysis
The sensemaking task in investigative analysis generates models that connect entities and events in an input stream of data. We describe two knowledge systems for aiding sensemaking in investigative analysis. The Spade system uses crime schemas to generate an explanatory hypothesis and past cases to validate the hypothesis. The STAB system represents crime schemas as hierarchical scripts with g...
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