LAW: A Workbench for Approximate Pattern Matching in Relational Data
by Wolverton, M. and Berry, P. and Harrison, I. and Lowrance, J. and Morley, D. and Rodriguez, A. and Ruspini, E. and Thomere, J.2003.
Note: in The Fifteenth Innovative Applications of Artificial Intelligence Conference (IAAI-03)
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.
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.
|Berry, Pauline M||Alumnus|
|Harrison, Ian W||Alumnus|
|Lowrance, John D||Program Director Emeritus|
|Morley, David N||Alumnus|
|Rodriguez, Andres C||Computer Scientist|
|Ruspini, Enrique H||Alumnus|
|Thomere, Jerome F||Computer Scientist|
|Wolverton, Michael J||Senior Computer Scientist|