Details
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New Feature
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Status: Closed
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Minor
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Resolution: Done
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Description
The proposed project extends https://issues.apache.org/jira/browse/SIS-97.
The Agent based modelling project during GSoC 2013 used a probabilistic model that was hardcoded. It served as the basis to predict criminal’s movements which infer crimes. This proposed project should do the inverse. Predict the probabilistic model that controls the criminals’ behavior using data about his movements and crimes.
The project should be preliminary work for data mining. From a sample anonymised emergency call (911 data) a criminal should be uniquely identified. Hidden Markov Model, a probabilistic state transition system, i.e., we define states such as “at home”, “in office etc”, “roaming mode” etc, and there are probabilistic transitions between them. We can associate some behavior to a particular state. Thus, the probabilistic model that was hardcoded by Nadeem (in GSOC 2013) was a Markov model (this is a little indirectly). When we only have the crime data and we want to find the model that dictates the criminal’s behavior, the Markov model is hidden to us. There are algorithms that can do this. These algorithms need to have their parameters set by humans – such as the number of states. So this would need some amount of experimentation.
