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Maps of sparse Markov chains efficiently reveal community structure in network flows with memory
[article]
2016
arXiv
pre-print
To better understand the flows of ideas or information through social and biological systems, researchers develop maps that reveal important patterns in network flows. In practice, network flow models have implied memoryless first-order Markov chains, but recently researchers have introduced higher-order Markov chain models with memory to capture patterns in multi-step pathways. Higher-order models are particularly important for effectively revealing actual, overlapping community structure, but
arXiv:1606.08328v1
fatcat:um5ixlkxmffebkkc3gaohmjxoq