Predicting crime

Predicting crime

Problem being addressed

Criminal activities are present in every aspect of human life in the world​,​ it has direct effects on quality of life as well as on socio-economic development of a nation. As it has become a major concern of almost all countries​,​ governments are prone to use advance technologies to tackle such issues.

Solution

A supervised learning technique to predict crimes with better accuracy. Machine learning agent can classify a criminal activity using basic details of a crime occurred in an area with time and location. The proposed system predicts crimes by analyzing dataset that contains records of previously committed crimes and their patterns.

Advantages of this solution

Using oversampling the researchers manage to achieve significant accuracy and show promising results in terms of predictive analytics.

Solution originally applied in these industries

government

Government Sector

Possible New Application of the Work

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Financial Sector

While researches in criminal activities are given priority in all over the world, in the future cyber crime prediction can be incorporated in the real world crime prediction, which will be of great value to the finance and banking sector.

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

Media

Social networks are often used as a potential source of criminal activity indicators, for example, twitter information can be used to find real time criminal offences. The same dataset can be used to find the concentration of crime occurrences, and find large scale of hotspots.

Author of original research described in this blitzcard:

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Name of the author who conducted the original research that this blitzcard is based on.

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