By Colleen McCue

It's now attainable to foretell the longer term by way of crime. In facts Mining and Predictive Analysis, Dr. Colleen McCue describes not just the chances for info mining to aid legislations enforcement pros, but additionally offers real-world examples exhibiting how facts mining has pointed out crime developments, expected neighborhood hot-spots, and sophisticated source deployment judgements. during this booklet Dr. McCue describes her use of "off the shelf" software program to graphically depict crime developments and to foretell the place destiny crimes tend to happen. Armed with this information, legislation enforcement executives can boost "risk-based deployment strategies," that let them to make expert and in your price range staffing judgements in line with the chance of particular felony activity.

Knowledge of complicated facts isn't a prerequisite for utilizing Data Mining and Predictive Analysis. The e-book is a kick off point for these pondering utilizing information mining in a legislation enforcement surroundings. It presents terminology, innovations, useful program of those strategies, and examples to focus on particular thoughts and methods in crime and intelligence research, which legislations enforcement and intelligence pros can tailor to their very own distinctive state of affairs and duties.

* Serves as a beneficial reference software for either the coed and the legislations enforcement professional
* includes sensible info utilized in real-life legislation enforcement situations
* method is particularly straight forward, conveying refined analyses in sensible phrases

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Extra resources for Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis

Example text

Similarly, almost everything that we work with in the operational environment also is a sample, because it is exceedingly rare that we can identify every single crime in a series or every piece of evidence. In many ways, it is like working with a less than perfect puzzle. We frequently are missing pieces, and it is not unusual to encounter a few additional pieces that do not even belong and try to incorporate them. Whether this is by chance, accident, or intentional misdirection on the part of the criminal, it can significantly skew our vision of the big picture.

5 In fact, evidence of recent victim drug use was extremely predictive in and of itself. The results of this study were rewarding in that they supported the idea that expert systems could be used to model violent crime. They also increased our knowledge about the relative degree of heterogeneity among drug-involved offenders, as well as the division of labor within illegal drug markets. Unfortunately, the findings were somewhat limited from an investigative standpoint. Generally, the motive helps determine a likely suspect; the “why” of a homicide often provides some insight into the “who” of a homicide.

When it turned out that the snipers were black, there was great surprise, particularly among the media. 2 Taking this information into consideration, we would not expect a 50:50 split along race lines when examining serial killers. 5 Errors 13 fewer black serial killers, if the distribution mirrored the overall population. Moreover, serial killers are relatively rare, which further confounds our calculations for reasons similar to those addressed earlier regarding small sample sizes and infrequent events.

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