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Publication Details

Helping Intelligence Analysts Detect Threats in Overflowing, Changing and Incomplete Information

by Thomere, J. and Harrison I. and Lowrance J. and Rodriguez A. and Ruspini E. and Wolverton M.

in Proceedings of the 2004 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety pp. 39-45,

Published by IEEE
Address: S. Giuliano - Venice, Italy
Organization: IEEE
Jul 2004.

Abstract

An important role of intelligence organizations is to be able to identity 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.

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Associated Projects

LAW

The Link Analysis Workbench

The goal of this project is to develop the Link Analysis Workbench (LAW), a Web-accessible tool where analysts and machines collaboratively perform link analysis by defining hierarchical and temporal patterns, that include uncertain and qualitative elements, and by defining search strategies for pattern application, through a graphical user interface that supports direct graphical browsing and editing of patterns, search strategies, and summaries and details of resulting matches.

AIC Personnel

Name Title E-mail
Harrison, Ian W Alumnus
Lowrance, John D Program Director
Rodriguez, Andres C Computer Scientist
Ruspini, Enrique H Alumnus
Thomere, Jerome F Computer Scientist
Wolverton, Michael J Senior Computer Scientist

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