ITR: COPLINK Center for Intelligence and Security Informatics Research---A Crime Data Mining Approach to Developing ôBorder Safeö Research

University Of Arizona, Tucson AZ

Investigators

Abstract

Abstract EIA-0326348 Hsinchun, Chen Title: ITR: COPLINK Center for Intelligence and Security Informatics Research- A Crime Data Mining Approach to Developing "Border Safe" Research. The main intended intellectual contribution of our research is three-fold: (a) developing new data mining, text mining, and knowledge discovery models and techniques that are motivated by law enforcement applications but can also be applied in other domains demonstrating similar characteristics, (b) developing new representations, models, and computational methods for scalable networks from other data mining applications, and (c) studying the acceptance and adoption of the developed crime data mining technologies in real-world settings and obtaining a comprehensive understanding of related policy implications including information sharing and privacy issues. The broader impacts of this research include: reducing cognitive and information overload in law enforcement applications; improving intelligence and law enforcement agencies' abilities to detect, prevent, and respond to crimes and terrorism events; fostering information sharing and collaboration among law enforcement agencies; and providing a large-scale research testbed for NSF KDD and "border safe" researches. The proposed research effort will leverage our highly successful past and ongoing work on the COPLINK system, our prior research experience on data mining, text mining, web computing, and information retrieval in other application domains, and our extensive ongoing partnerships with local, state, and federal law enforcement agents.