(Georgia Institute of Technology, 2010)
Goel, Ashok K.; Sinharoy, Avik; Adams, Summer; Dokania, Adity
The sensemaking task in investigative analysis generates stories that connect entities and events in an input stream of data. The Stab system represents crime stories as hierarchical scripts with goals and states. It generates multiple stories as 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. In this report, we describe Stab2, a new interactive version of the knowledge‐based Stab system. Stab2 contains a story editor that enables users to enter and edit crime stories. We illustrate Stab2 with examples from the IEEE VAST contest datasets.
(Georgia Institute of Technology, 2009)
Goel, Ashok K.; Adams, Summer; Cutshaw, Neil; Sugandh, Neha
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 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 and Spade
as automated cognitive assistants to human analysts: they may support sensemaking in investigative
analysis by generating and managing multiple competing hypotheses.