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Mutualistic networks are used to study the structure and processes inherent to mutualistic relationships. In this paper, we introduce a random matrix ensemble (RME) representing the adjacency matrices of mutualistic networks composed by two…

Disordered Systems and Neural Networks · Physics 2021-11-10 C. T. Martínez-Martínez , J. A. Méndez-Bermúdez , Thomas Peron , Yamir Moreno

Graph is an abstract representation commonly used to model networked systems and structure. In problems across various fields, including computer vision and pattern recognition, and neuroscience, graphs are often brought into comparison (a…

Optimization and Control · Mathematics 2022-03-04 Quoc Van Tran , Hyo-Sung Ahn

We define and study the link prediction problem in bipartite networks, specializing general link prediction algorithms to the bipartite case. In a graph, a link prediction function of two vertices denotes the similarity or proximity of the…

Machine Learning · Computer Science 2010-07-27 Jérôme Kunegis , Ernesto W. De Luca , Sahin Albayrak

In this article, we extend several algebraic graph analysis methods to bipartite networks. In various areas of science, engineering and commerce, many types of information can be represented as networks, and thus the discipline of network…

Discrete Mathematics · Computer Science 2015-01-16 Jérôme Kunegis

We completely determine the spectrum of an $I$-graph, that is, the eigenvalues of its adjacency matrix. We apply our result to prove known characterizations of connectedness and bipartiteness in $I$-graphs by using an spectral approach.…

Combinatorics · Mathematics 2015-11-12 Allana S. S. de Oliveira , Cybele T. M. Vinagre

Bipartite networks manifest as a stream of edges that represent transactions, e.g., purchases by retail customers. Many machine learning applications employ neighborhood-based measures to characterize the similarity among the nodes, such as…

Social and Information Networks · Computer Science 2018-05-09 Nesreen K. Ahmed , Nick Duffield , Liangzhen Xia

We propose a random bipartite graph with weights assigned to both parts of the vertex sets. Edges are formed independently with probabilities that depend on these weights. This bipartite graph naturally gives rise to a random intersection…

Probability · Mathematics 2025-06-10 Alastair Haig , Minmin Wang

Let $G_S$ be a graph with loops obtained from a graph $G$ of order $n$ and loops at $S \subseteq V(G)$. In this paper, we establish a neccesary and sufficient condition on the bipartititeness of a connected graph $G$ and the spectrum…

Combinatorics · Mathematics 2023-04-12 Saieed Akbari , Hussah Al Menderj , Miin Huey Ang , Johnny Lim , Zhen Chuan Ng

For graphs $G$ and $H$, an {\em $H$-colouring} of $G$ (or {\em homomorphism} from $G$ to $H$) is a function from the vertices of $G$ to the vertices of $H$ that preserves adjacency. $H$-colourings generalize such graph theory notions as…

Combinatorics · Mathematics 2012-06-15 John Engbers , David Galvin

Connectedness and bipartiteness are basic properties of classical graphs, and the purpose of this paper is to investigate the case of quantum graphs. We introduce the notion of connectedness and bipartiteness of quantum graphs in terms of…

Operator Algebras · Mathematics 2024-07-31 Junichiro Matsuda

Let $q=p^e$, where $p$ is a prime and $e\geq 1$ is an integer. For $m\geq 1$, let $P$ and $L$ be two copies of the $(m+1)$-dimensional vector spaces over the finite field $\mathbb{F}_q$. Consider the bipartite graph $W_m(q)$ with partite…

Combinatorics · Mathematics 2014-02-17 Sebastian M. Cioabă , Felix Lazebnik , Weiqiang Li

We study the properties of random graphs where for each vertex a {\it neighbourhood} has been previously defined. The probability of an edge joining two vertices depends on whether the vertices are neighbours or not, as happens in Small…

Disordered Systems and Neural Networks · Physics 2009-11-10 Sebastian Risau-Gusman

In this paper we study the local law for eigenvalues of large random regular bipartite graphs with degree growing arbitrarily fast. We prove that the empirical spectral distribution of the adjacency matrix converges to a scaled down copy of…

Combinatorics · Mathematics 2013-10-18 Linh V. Tran

Although the spectral properties of random graphs have been a long-standing focus of network theory, the properties of right eigenvectors of directed graphs have so far eluded an exact analytic treatment. We present a general theory for the…

Disordered Systems and Neural Networks · Physics 2021-03-12 Fernando L. Metz , Izaak Neri

We show that if the two parts of a finite bipartite graph have the same degree sequence, then there is a bipartite graph, with the same degree sequences, which is symmetric, in that it has an involutive graph automorphism that interchanges…

Combinatorics · Mathematics 2014-07-07 Grant Cairns , Stacey Mendan

The second largest eigenvalue of a graph is an important algebraic parameter which is related with the expansion, connectivity and randomness properties of a graph. Expanders are highly connected sparse graphs. In coding theory, Expander…

Combinatorics · Mathematics 2023-08-23 Machasri Manickam , Kalyani Desikan

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short range correlations in the level spacings of the…

Physics and Society · Physics 2017-06-08 Carl P. Dettmann , Orestis Georgiou , Georgie Knight

We enumerate factorisations of the complete bipartite graph into spanning semiregular graphs in several cases, including when the degrees of all the factors except one or two are small. The resulting asymptotic behaviour is seen to…

Combinatorics · Mathematics 2022-12-21 Mahdieh Hasheminezhad , Brendan D. McKay

If a vertex $v$ in a graph $G$ has degree larger than the average of the degrees of its neighbors, we call it a groupie in $G$. In the current work, we study the behavior of groupie in random multipartite graphs with the link probability…

Combinatorics · Mathematics 2012-09-18 Marius Portmann , Hongyun Wang

We perform an extensive investigation of the localization properties of the eigenmodes of the Laplace and adjacency matrix for one-dimensional random geometric graphs. We evaluate the density of states, the probability distribution of the…

Disordered Systems and Neural Networks · Physics 2025-08-27 Luca Schaefer , Barbara Drossel