id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-026306-mkmrninv	Lepskiy, Alexander	Belief Functions for the Importance Assessment in Multiplex Networks	2020-05-15		.txt	text/plain	4133	274	61	The measures use the combination of "high", "low" and "(high, low)" probabilities of the influence based on weighted and unweighted degrees of nodes via Dempster's rule. Secondly, one can aggregate connections between pairs of nodes to obtain monoplex network and then apply centrality measures to a new weighted graph. In this Section we describe a graph model with one layer of interaction as well as the construction of centrality measure based on a mass function for a network. Additionally, if we consider a 1-neighborhood of nodes in multiplex acyclic graphs with two layers then the following propositions concerning the aggregated interaction centrality value can be proved. We apply Dempster-Shafer theory in order to reveal key elements in undirected weighted graphs as well as to aggregate interactions between nodes into the total ranking. If nodes cooperate with each other on different levels of interactions then we apply a combination rule to mass functions obtained for different layers of a multiplex structure.	./cache/cord-026306-mkmrninv.txt	./txt/cord-026306-mkmrninv.txt