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Publication in EndNote Format

%0 Generic %A Wolverton, M. and Berry, P. and Harrison, I. and Lowrance, J. and Morley, D. and Rodriguez, A. and Ruspini, E. and Thomere, J. %T LAW: A Workbench for Approximate Pattern Matching in Relational Data %D 2003 %X Pattern matching for intelligence organizations is a challenging problem. The data sets are large and noisy, and there is a flexible and constantly changing notion of what constitutes a match. We are developing the Link Analysis Workbench (LAW) to assist an expert user in the intelligence community in creating and maintaining patterns, matching those patterns against a large collection of relational data, and manipulating partial results. This paper describes two key facets of the LAW system: (1) a pattern-matching module based on a graph edit distance metric, and (2) a system architecture that supports the integration and tasking of multiple pattern matching modules based on their capabilities and the specific problem at hand. %O in The Fifteenth Innovative Applications of Artificial Intelligence Conference (IAAI-03) %U http://www.ai.sri.com/pubs/files/931.pdf

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