Annotated Bibliography for the DEWPOINT project

This bibliography covers aspects of the Detection and Early Warning of Proliferation from Online INdicators of Threat (DEWPOINT) project including 1) data management and querying, 2) baseline and advanced methods for classifying free text, and 3) algorithms to achieve the ultimate goal of inferring intent from free text sources. Metrics for assessing the quality and correctness of classification are addressed in the second group. Data management and querying include methods for efficiently storing, indexing, searching, and organizing the data we expect to operate on within the DEWPOINT project

A Semi-supervised Algorithm for Pattern Discovery in Information Extraction from Textual Data

In this article we present a semi-supervised algorithm for pattern discovery in information extraction from textual data. The patterns that are discovered take the form of regular expressions that generate regular languages. We term our approach `semi-supervised' because it requires significantly less effort to develop a training set than other approaches. From the training data our algorithm automatically generates regular expressions that can be used on previously unseen data for information extraction. Our experiments show that the algorithm has good testing performance on many features that are important in the fight against terrorism