Xin Wang

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We develop and investigate probabilistic approaches of state clustering in higher-order Markov chains. A direct extension of the Aggregate Markov model to higher orders turns out to be problematic due to the large number of parameters required. However, in many cases, the events in the finite memory are not equally salient in terms of their pre-dictive(More)
Predictive modelling of online dynamic user-interaction recordings and community identification from such data becomes more and more important with the widespread use of online communication technologies. Despite of the time-dependent nature of the problem, existing approaches of community identification are based on static or fully observed network(More)
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