Crime prediction
Hierarchical Spatio-Temporal Pattern Discovery and Predictive Modeling
Effect of Weather and Temporal Variations on Calls for Police Service
Crime and Justice: A Review of Research, Volume 32
Normative Forecasting - An Application of Stochastic Models to Crime Rates
Proactive Policing: Using Geographic Analysis to Fight Crime
Place as the Focal Point: Developing a Theory for the DDACTS Model
Predicting Rapist Type From Crime-Scene Variables
Compstat and Organizational Change in the Lowell Police Department: Challenges and Opportunities
Specifying the Relationship Between Arrestee Drug Test Results and Recidivism
Experimenting with Future-Oriented Analysis at Crime Hot Spots in Minneapolis
Implementing DDACTS in Baltimore County: Using Geographic Incident Patterns to Deploy Enforcement
Risk Terrain Modeling for Spatial Risk Assessment
Including Tourists in Crime Rate Calculations for New Casino Jurisdictions: What Difference Does It Make?
Importance of Both Opportunity and Social Disorganization Theory in a Future Research Agenda to Advance Criminological Theory and Crime Prevention at Places
Considering Lead Poisoning as a Criminal Defense
Predicting Demand for Service for Future Developments
Integrating Crime and Traffic Crash Data in Nashville
Geography and Public Safety: A Quarterly Bulletin of Applied Geography for the Study of Crime and Public Safety, Volume 2, Issue 4
Real-Time Crime Forecasting Challenge Webinar
This webinar will offer a brief overview of the National Institute of Justice and the data science needs of the criminal justice field. In addition, it will provide details about the Crime Forecasting Challenge, including who can submit, how to retrieve datasets, and the submission categories. The overall goal of the Crime Forecasting Challenge is to harness recent advances in data science to drive innovation in algorithms that advance place-based crime forecasting.
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