Automated Detection of Terrorist Activities through Link Discovery within Massive Datasets

Christopher M. Boner

This paper describes link discovery technology that is designed to detect threat activities by extracting and piecing together transactional evidence from massive datasets that are composed mostly of noise and clutter. The approach is an integration of several innovative component technologies, including partial pattern matching, hypothesis evaluation and hypothesis merging.

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