Suresh Marru created SIS-324:
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Summary: 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
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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