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https://issues.apache.org/jira/browse/SIS-324?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Martin Desruisseaux updated SIS-324:
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Priority: Minor (was: Major)
> Develop Hidden Markov Model to predict criminal moments
> ---------------------------------------------------------
>
> Key: SIS-324
> URL: https://issues.apache.org/jira/browse/SIS-324
> Project: Spatial Information Systems
> Issue Type: New Feature
> Reporter: Suresh Marru
> Priority: Minor
>
> 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.
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