8/21/2011

Predicting where crime will occur to help fight crime

From Government Technology:

The project uses an algorithm that is similar to what’s used for predicting earthquake aftershocks. “There’s a belief that certain crime types — in this case, burglaries and vehicle thefts — can be predicted in the same way,” said Zach Friend, the Santa Cruz Police Department’s press information officer and principal management analyst.

The algorithm was developed by George Mohler, an assistant professor in the Department of Mathematics and Computer Science at Santa Clara University in California. The Santa Cruz Police Department reached out to Mohler after reading about the algorithm in the Los Angeles Times.

The Police Department worked with Mohler for six months starting in October 2010 to develop the project for real-world implementation. Since the model had already been created through grant funding, the department didn’t have to pay to use it.

For the six-month pilot, the Police Department pulls crime data every day from its record management system that tracks crime that’s been reported in the city. The data is put into a spreadsheet and geo-coded and then run through Mohler’s Web-based computer algorithm. . . .

In the nearly two months of use, the pilot has garnered positive results. Since the pilot’s deployment, the model has correctly predicted 40 percent of the crimes that it was aiming to predict, and the Santa Cruz Police Department has seen a reduction in the types of crime that it’s been addressing.

In addition, the Police Department saw a 27 percent decrease in the number of reported burglaries in July compared with July 2010. Friend said the department won’t know how successful the model is until it’s been running for at least three months. . . .


Thanks to Jeff Yager for the link.

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1 Comments:

OpenID DougHuffman said...

I believe that this is the paper mentioned.

http://math.scu.edu/~gmohler/geopro_siap.pdf

I am coincidentally enjoying my introduction to Bayesian epistemology and inference just now.

Waiting on ET Jaynes' Probability Theory: The Logic of Science

8/22/2011 7:38 AM  

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