A Visual Analytics Approach for Crime Signature Generation and Exploration
Wolfgang Jentner, Geoffrey P. Ellis, Florian Stoffel, Dominik Sacha, Daniel A. Keim · KOPS (University of Konstanz) · 2016
The exploration of volumes of crime reports is a tedious task in crime intelligence analysis, given the largely unstructured nature of the crime descriptions. This paper describes a Visual Analytics approach for crime signature exploration that tightly integrates automated event sequence extraction and signature mining with interactive visualization. We describe the major components of our analysis pipeline — crime concept/event extraction, crime sequence mining, and interactive visualization. We illustrate its applicability with a real world use case. Finally, we discuss current problems, future plans, and open challenges in our development of a solution that incorporates automated event pattern mining with human expert feedback.