Data Mining and Predictive Analysis. Intelligence Gathering by Colleen McCue (Auth.)

By Colleen McCue (Auth.)

Content material:

, Pages xiii-xiv

, Pages xv-xxiii

, Pages xxv-xxxi
1 - Basics

, Pages 3-18
2 - area Expertise

, Pages 19-24
3 - info Mining

, Pages 25-41
4 - approach versions for information Mining and Analysis

, Pages 45-66
5 - Data

, Pages 67-92
6 - Operationally appropriate Preprocessing

, Pages 93-115
7 - Predictive Analytics

, Pages 117-141
8 - Public Safety-Specific Evaluation

, Pages 143-163
9 - Operationally Actionable Output

, Pages 165-174
10 - basic Crime

, Pages 177-185
11 - Behavioral research of Violent Crime

, Pages 187-213
12 - danger and risk Assessment

, Pages 215-235
13 - Deployment

, Pages 239-265
14 - Surveillance Detection

, Pages 267-298
15 - complex Topics

, Pages 301-313
16 - destiny Trends

, Pages 315-321

, Pages 323-332

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Extra info for Data Mining and Predictive Analysis. Intelligence Gathering and Crime Analysis

Example text

Data mining is not a vast repository designed to maintain extensive files containing both public and private records on each and every American, as has been suggested by some. It is an analytical tool. If people are concerned about privacy issues, then they should focus on the availability of and access to sensitive data resources, not the analytical tools. Banning an analytical tool because of fear that it will be misused is similar to banning pocket calculators because some people use them to cheat on their taxes.

2 Confirmation and Discovery 29 then used, modified, and refined during the investigation of subsequent cases. Analysts and investigators will look for similarities and known patterns to identify possible motives and likely suspect characteristics when confronted with a new case. This information is then used to understand the new case and investigate it. These internal rule sets also allow an investigator to select suspects, guide interviews and interrogations, and ultimately solve a case. These existing rule sets can be evaluated, quantified, or “confirmed” using data mining.

Similarly, who better to distinguish between suspicious data and data that are both valid and reliable? The answer to all three questions is operational personnel. Our sworn partners in the good fight are perfectly suited in many ways to do our jobs as analysts, or at least to partner more closely with us in the analytical process. 2 Domain Expertise for Analysts Analysts that spend all of their time in front of a computer can become so separated from the data and end users that they have little value to the organization.

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