LAW: A Workbench for Approximate Pattern Matching in Relational Data

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.

• Type: Conference
• Year: 2003
• Where: IAAI
• Authors: Michael Wolverton, Pauline Berry, Ian W. Harrison, John D. Lowrance, David N. Morley, Andres C. Rodriguez, Enrique H. Ruspini, Jérôme Thoméré
• Keywords: Artificial Intelligence, IAAI 2003, Link Analysis Workbench, Pattern Matching, Pattern Matching Modules