Andres C. Rodriguez

Helping intelligence analysts detect threats in overflowing, changing and incomplete information

An important role of intelligence organizations is to be able to identify and predict threats within a vast quantity of imprecise and noisy information. We describe the concept and function of our pattern-matching architecture, LAW (Link Analysis Workbench). This system is based upon two main ideas. The first idea is that both the data and the threats can be described in term of graphs of entities and events linked together with semantic relationships. Therefore, graph-based pattern matching techniques can be used to identify threats. The second idea is that analysts constitute an essential part of the system; LAW is designed to handle a lot of interaction with the user, particularly to help in authoring and revising patterns, by allowing analysts to understand the matching process and results.

Angler: a collaborative tool for cognitive expansion

Humans tend to bias the analysis of situations based on their previous experiences and back-ground. Angler is a tool to help analysts explore, understand, and overcome such biases and to collaborate in expanding their joint cognitive vision. Angler utilizes divergent and convergent techniques, such as brainstorming and clustering or voting, to guide a diverse set of intelligence professionals in completing a complex knowledge task. The tool helps the group through the process of forming consensus, while preserving and quantifying differing ways of thinking. Angler provides a Web-based collaborative environment that allows users distributed by both time and geography to assemble in teams, with the help of a facilitator.