A Software System for Information Extraction in Criminal Justice Information Systems

This project will build an information extraction system that automatically extracts features from textual data commonly used by law enforcement agencies. Such valuable information, highly useful in criminal investigation, is often not stored in a database in relational form. This project's technology is capable of automatically extracting such information from the source text and automatically entering the information into a fielded, relational database. The extracted information can thus be readily retrieved and compared with other database records using modern computer-based information retrieval systems. The technique used significantly shortens the time needed to train an information extraction system of this nature. The learning algorithm for rule discovery requires less knowledge engineering than existing systems. This approach enables the extraction of such features for use in everyday search and retrieval applications such as suspect identification. This system will provide input to advanced text mining algorithms for pattern detection. Such algorithms can be used, for example, to map modus operandi to physical descriptions of criminal suspects.