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Home / Proceedings / Proceedings of the AAAI Conference on Innovative Applications of Artificial Intelligence Conference, 15 / Book One

LAW: A Workbench for Approximate Pattern Matching in Relational Data

February 1, 2023

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Authors

Michael Wolverton

Pauline Berry

Ian Harrison

John Lowrance

David Morley

Andres Rodriguez

Enrique Ruspini

and Jerome Thomere

DOI:


Abstract:

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.

Topics: AAAI

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Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere LAW: A Workbench for Approximate Pattern Matching in Relational Data Proceedings of the AAAI Conference on Innovative Applications of Artificial Intelligence Conference, 15 (2003) 143.

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere LAW: A Workbench for Approximate Pattern Matching in Relational Data IAAI 2003, 143.

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere (2003). LAW: A Workbench for Approximate Pattern Matching in Relational Data. Proceedings of the AAAI Conference on Innovative Applications of Artificial Intelligence Conference, 15, 143.

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere. LAW: A Workbench for Approximate Pattern Matching in Relational Data. Proceedings of the AAAI Conference on Innovative Applications of Artificial Intelligence Conference, 15 2003 p.143.

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere. 2003. LAW: A Workbench for Approximate Pattern Matching in Relational Data. "Proceedings of the AAAI Conference on Innovative Applications of Artificial Intelligence Conference, 15". 143.

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere. (2003) "LAW: A Workbench for Approximate Pattern Matching in Relational Data", Proceedings of the AAAI Conference on Innovative Applications of Artificial Intelligence Conference, 15, p.143

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere, "LAW: A Workbench for Approximate Pattern Matching in Relational Data", IAAI, p.143, 2003.

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere. "LAW: A Workbench for Approximate Pattern Matching in Relational Data". Proceedings of the AAAI Conference on Innovative Applications of Artificial Intelligence Conference, 15, 2003, p.143.

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere. "LAW: A Workbench for Approximate Pattern Matching in Relational Data". Proceedings of the AAAI Conference on Innovative Applications of Artificial Intelligence Conference, 15, (2003): 143.

Michael Wolverton|| Pauline Berry|| Ian Harrison|| John Lowrance|| David Morley|| Andres Rodriguez|| Enrique Ruspini|| and Jerome Thomere. LAW: A Workbench for Approximate Pattern Matching in Relational Data. IAAI[Internet]. 2003[cited 2023]; 143.


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