Helping Intelligence Analysts Make Connections

Hossain, Mahmud Shahriar (Virginia Tech) | Andrews, Christopher (Virginia Tech) | Ramakrishnan, Naren (Virginia Tech) | North, Chris (Virginia Tech)

AAAI Conferences 

Discovering latent connections between seemingly unconnected documents and constructing "stories" from scattered pieces of evidence are staple tasks in intelligence analysis. We have worked with government intelligence analysts to understand the strategies they use to make connections. Beyond techniques like clustering that aim to provide an initial broad summary of large document collections, an important goal of analysts in this domain is to assimilate and synthesize fine grained information from a smaller set of foraged documents. Further, analysts' domain expertise is crucial because it provides rich contextual background for making connections and thus the goal of KDD is to augment human discovery capabilities, not supplant it. We describe a visual analytics system we have built - Analyst's Workspace (AW) - that integrates browsing tools with a storytelling algorithm in a large screen display environment. AW helps analysts systematically construct stories of desired fidelity from document collections and helps marshall evidence as longer stories are constructed.

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