I have watched the developing debate around attempts to predict for a long time, which has become part of the so-called intelligence-led policing model and can be cited as a gain from using analysis / data-mining.
Taken from a paper by a US data-mining presentation:Link:http://www.detecter.eu/index.php?opt...&id=7&Itemid=9 within summary of the Zurich meeting on data mining.X PD used data mining as a tool for determining how best to position police assets in anticipation of crime. Allocating assets so as to increase police presence where a particular incident is expected, for example, might help to prevent crime. She provided two examples of what she considered to be effective data analysis. One involved the application of supervised learning to the problem of random gun fire on New Year’s Eve. Data analysis was used to identify the times and places where the most incidents occurred. This information permitted local police to deploy officers strategically, resulting in a 47% reduction in the number of reported incidents and a reduction in personnel costs.
One of the biggest issues around prediction and analysis is the data available, there is a considerable difference between actual / reported / recorded incidents and crimes. In the UK for example to officers dismay a large proportion of house burglaries are not reported. We have learnt, sometimes painfully, that low-level quality of life issues are far more important to the public than what the police want to do, such as "fighting crime".
Bookmarks