dr. rado kotorov technical director strategic product mgt. bi applications for crime intelligence :...
TRANSCRIPT
Dr. Rado KotorovTechnical Director Strategic Product Mgt.
BI Applications For Crime Intelligence : Data Mining & Predictive Modeling
Forward Looking BI with Predictive Analytics
Past Events
Reporting & Analysis
Future Events
Predictive Modeling
Re-active Actions• Events have occurred• Analyze cause• Adjust processes to
prevent
Pro-active Actions• Events have not occurred • Expect when & where• Allocate resources to
prevent
Forward Looking BI: Answer a Different Set of Questions
Degree of Intelligence
Standard Reports
Ad Hoc Reports
Query/Drill Down
KPIs/Alerts
What happened?
How many, how often, where?
Where exactly is the problem?
What actions are needed?
Rea
r V
iew
Statistical Analysis
Forecasting/Extrapolation
Predictive Modeling
Optimization
Why is this happening?
What of these trends continue?
What will happen next?
What is the best that can happen?
Fo
rwar
d V
iew
Note: Adapted from “Competing on Analytics”
Copyright 2007, Information Builders. Slide 4
How Does Predictive Analytics Help You Make Better Decisions: Issue 1
Situation: Large volumes of historical data
Issue: How
do you determine what the right pattern is
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f(x) = 1414.48364432662 x + 25797.6679752176R² = 0.837793629857125
Crimes
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How Does Predictive Analytics Help You Make Better Decisions: Issue 2
Situation: Large number of variables for analysis
Issue: How do you determine which variables are more important.Not all factors have
equal weightsThe more factors the
harder to determine their weights
Number of Crimes
Number of Officers
WeatherConditions
Unknown
Economic Factors
Crime
Community Events
Demographics
Copyright 2007, Information Builders. Slide 6
Predictive Modeling and Scoring Applications
Predictive Modeling: Predictive modeling is a process that: (1) takes as input historical data, (2) evaluates it statistically to detect hidden patterns in it, and (3) derives a formula or set of rules that describe the uncovered patterns, referred to also as a model.
-- A pattern can be a relationship or an outcome
Scoring Application: A scoring application automates the use of the model on new records in order to predict relationships and outcome probabilities.
-- Relationship: higher unemployment rates increase crimes in lower income areas
-- Outcome: There is a high probability of aggravated assault occurring in dispatch zone X
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It is useful where operational users have to make
decisions that involve uncertainty and risk.
It estimates the probabilities associated with the expected events, i.e., the likelihood that the event will occur.
The probability estimates help managers make better decisions than guessing.
When Is a Scoring Application Useful?
Everyone Makes Decisions Abut the Future
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When?
Where?
Correlated Events?
DispatchPatrol Cars
Gut feeling or science?
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Predicting Crime
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Time and location of future incidence in a crime pattern or series Identify individuals who are likely to reoffend Inmate radicalization risk assessment (i.e., identify inmates who are in danger) Drug market displacement (i.e., where next open air drug market will pop up) Disorder and environmental variables Likely impact of specific operations. Disruption of criminal organization (criminal leadership) Prediction of criminal adaptation (not only law enforcement efforts but also media, etc.) Data analysis and support of crime suppression analysis Patrol staffing and resources allocation Localized crime spikes Identify juveniles likely to be involved in violent crime Risk assessment of sex offending in juveniles Early identifications of career criminals Identify victims of unreported crimes Evaluation of interventions Impact of drug enforcement on markets and allied crimes Identification and analysis of crime-prone events and locations Individual-specific analysis Travel of serial offenders
Possible Use & Value of Predictive Policing From 1st Annual NIJ Predictive Policing Symposium
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Analysis of predatory patterns Correlation of environmental factors outside of crime like weather Threat and vulnerability assessment Prioritization of sources Unstructured data extraction (police reports, blogs, incident reports and social networks) Predicting acts of terror Predicting riots Social network analysis Video analytics (including behavioralistics) Use of NIBRS to help prediction Wide-area surveillance for video fusion Precursors and leading indicators to crime (including non-obvious predictors) City/neighborhood planning Design of spaces; economic development; security resource allocation; infrastructure protection Offender monitoring, predicting behavior, endpoint sentencing Traffic management, crowd control Management of police personnel Professional development, recruitment Risk for excessive use-of-force, discipline
Possible Use & Value of Predictive Policing From 1st Annual NIJ Predictive Policing Symposium
Process For Building And Deploying Predictive Applications
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CRISP-DM Process Model ( http://www.crisp-dm.org )
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RStat: Differentiators & Benefits
Based on R-Project Open Source Maintained by world wide consortium of universities, scientists,
government funded research organizations, statisticians. Over 2000 packages
RStat is a GUI to R Intuitive guided approach to modeling Simple model evaluation Intended both for business analysts and advanced modelers
Single BI and Predictive Modeling Environment Re-use metadata and queries Perform data manipulation and sampling Build scoring applications
Unique Deployment Method for Scoring Solutions Scoring models are built directly into WF metadata Deployment on any platform and operating system - Windows, Unix,
Linux, Z/OS, and i Series.
Copyright 2007, Information Builders. Slide 14
Thank you