• Corpus ID: 220363546

Learning the Markov order of paths in a network

  title={Learning the Markov order of paths in a network},
  author={Luka V. Petrovi'c and Ingo Scholtes},
We study the problem of learning the Markov order in categorical sequences that represent paths in a network, i.e. sequences of variable lengths where transitions between states are constrained to a known graph. Such data pose challenges for standard Markov order detection methods and demand modelling techniques that explicitly account for the graph constraint. Adopting a multi-order modelling framework for paths, we develop a Bayesian learning technique that (i) more reliably detects the… 

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