The Google matrix G of a directed network is a stochastic square matrix with nonnegative matrix elements and the sum of elements in each column being equal to unity. This matrix describes a Markov chain (Markov, 1906-a) of transitions of a random surfer performing jumps on a network of nodes connected by directed links. The network is characterized by an adjacency matrix Aij with elements Aij=1 if node j points to node i and zero otherwise. The matrix of Markov transitions Sij is constructed from the adjacency matrix Aij by normalization of the sum of column elements to unity and replacing columns with only zero elements (dangling nodes) with equal elements 1/N where N is the matrix size (number of nodes). Then the elements of the Google ma...
AbstractUsing combinatorial and analytic techniques, we give conditioning bounds for the stationary ...
Abstract. We present a simple algorithm for computing the PageRank (stationary distribution) of the ...
Many notions of network centrality can be formulated in terms of invariant probability vectors of su...
The Google matrix G of a directed network is a stochastic square matrix with nonnegative matrix elem...
In the past decade modern societies have developed enormous communication and social networks. Their...
For DNA sequences of various species we construct the Google matrix [Formula: see text] of Markov tr...
For DNA sequences of various species we construct the Google matrix G of Markov transitions between ...
We construct and study the Google matrix of Bitcoin transactions during the time period from the ver...
11 pages, 8 pdf figures; additional material available at: http://www.quantware.ups-tlse.fr/QWLIB/li...
The spectral and Jordan structures of the web hyperlink matrix G(c) = cG + (1 − c)evT have been anal...
9+ pages. 12 figsInternational audienceWe introduce a number of random matrix models describing the ...
For a good simulation it is very important to find methods for navigating through the web (Levene an...
Cette thèse s’intéresse à l’analyse du réseau dirigé extrait de la structure des hyperliens de Wikip...
The resource network is a non-linear threshold model where vertices exchange resource in infinite di...
Additional file 3: Network display methods 2. Network display of transition matrices for $$N=20, \mu...
AbstractUsing combinatorial and analytic techniques, we give conditioning bounds for the stationary ...
Abstract. We present a simple algorithm for computing the PageRank (stationary distribution) of the ...
Many notions of network centrality can be formulated in terms of invariant probability vectors of su...
The Google matrix G of a directed network is a stochastic square matrix with nonnegative matrix elem...
In the past decade modern societies have developed enormous communication and social networks. Their...
For DNA sequences of various species we construct the Google matrix [Formula: see text] of Markov tr...
For DNA sequences of various species we construct the Google matrix G of Markov transitions between ...
We construct and study the Google matrix of Bitcoin transactions during the time period from the ver...
11 pages, 8 pdf figures; additional material available at: http://www.quantware.ups-tlse.fr/QWLIB/li...
The spectral and Jordan structures of the web hyperlink matrix G(c) = cG + (1 − c)evT have been anal...
9+ pages. 12 figsInternational audienceWe introduce a number of random matrix models describing the ...
For a good simulation it is very important to find methods for navigating through the web (Levene an...
Cette thèse s’intéresse à l’analyse du réseau dirigé extrait de la structure des hyperliens de Wikip...
The resource network is a non-linear threshold model where vertices exchange resource in infinite di...
Additional file 3: Network display methods 2. Network display of transition matrices for $$N=20, \mu...
AbstractUsing combinatorial and analytic techniques, we give conditioning bounds for the stationary ...
Abstract. We present a simple algorithm for computing the PageRank (stationary distribution) of the ...
Many notions of network centrality can be formulated in terms of invariant probability vectors of su...