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A network-theoretic approach for determining the complexity of a graph is proposed. This approach is based on the relationship between the linear algebra (theory of determinants) and the graph theory. In this paper we contribute a new…

Discrete Mathematics · Computer Science 2018-12-04 E. M. Badr , B. Mohamed

The purpose of this paper is to analyze the degree index and clustering index in random graphs. The degree index in our setup is a certain measure of degree irregularity whose basic properties are well studied in the literature, and the…

Probability · Mathematics 2026-03-11 Ümit Işlak , Barış Yeşiloğlu

Complex systems, ranging from soft materials to wireless communication, are often organised as random geometric networks in which nodes and edges evenly fill up the volume of some space. Studying such networks is difficult because they…

Probability · Mathematics 2022-07-19 Ivan Kryven , Rik Versendaal

We propose a model for evolving networks by merging building blocks represented as complete graphs, reminiscent of modules in biological system or communities in sociology. The model shows power-law degree distributions, power-law…

Statistical Mechanics · Physics 2009-11-11 Kazuhiro Takemoto , Chikoo Oosawa

We consider 15 properties of labeled random graphs that are of interest in the graph-theoretical and the graph mining literature, such as clustering coefficients, centrality measures, spectral radius, degree assortativity, treedepth,…

Social and Information Networks · Computer Science 2022-06-24 Hang Chen , Vahan Huroyan , Stephen Kobourov , Myroslav Kryven

Link prediction is a fundamental problem in graph theory with diverse applications, including recommender systems, community detection, and identifying spurious connections. While feature-based methods achieve high accuracy, their reliance…

Social and Information Networks · Computer Science 2025-01-14 Mehrdad Rafiepour , S. Mehdi Vahidipour

We present a system called Dist-$\mu$-RA for the distributed evaluation of recursive graph queries. Dist-$\mu$-RA builds on the recursive relational algebra and extends it with evaluation plans suited for the distributed setting. The goal…

Databases · Computer Science 2025-04-01 Sarah Chlyah , Pierre Genevès , Nabil Layaïda

Network growth as described by the Duplication-Divergence model proposes a simple general idea for the evolution dynamics of natural networks. In particular it is an alternative to the well known Barab\'asi-Albert model when applied to…

Property graphs can be used to represent heterogeneous networks with labeled (attributed) vertices and edges. Given a property graph, simulating another graph with same or greater size with the same statistical properties with respect to…

Social and Information Networks · Computer Science 2019-07-18 Arun V. Sathanur , Sutanay Choudhury , Cliff Joslyn , Sumit Purohit

Complex networks have gained more attention from the last few years. The size of real-world complex networks, such as online social networks, WWW network, collaboration networks, is increasing exponentially with time. It is not feasible to…

Social and Information Networks · Computer Science 2019-10-08 Akrati Saxena , Vaibhav Malik , S. R. S. Iyengar

In this paper, we study the joint behaviour of the degree, depth and label of and graph distance between high-degree vertices in the random recursive tree. We generalise the results obtained by Eslava and extend these to include the labels…

Probability · Mathematics 2023-01-31 Bas Lodewijks

We solve the graph bi-partitioning problem in dense graphs with arbitrary degree distribution using the replica method. We find the cut-size to scale universally with <k^1/2>. In contrast, earlier results studying the problem in graphs with…

Disordered Systems and Neural Networks · Physics 2008-12-11 Joerg Reichardt , Stefan Bornholdt

Graphlets are subgraphs rooted at a fixed vertex. The number of occurrences of graphlets aligned to a particular vertex, called graphlet degree sequence (gds), gives a topological description of the surrounding of the analyzed vertex.…

Combinatorics · Mathematics 2026-01-01 David Hartman , Aneta Pokorná , Daniel Trlifaj , Lluís Vena

We study a number of graph exploration problems in the following natural scenario: an algorithm starts exploring an undirected graph from some seed node; the algorithm, for an arbitrary node $v$ that it is aware of, can ask an oracle to…

Data Structures and Algorithms · Computer Science 2017-10-25 Flavio Chierichetti , Shahrzad Haddadan

A great deal of effort has been spent measuring topological features of the Internet. However, it was recently argued that sampling based on taking paths or traceroutes through the network from a small number of sources introduces a…

Disordered Systems and Neural Networks · Physics 2008-04-12 Aaron Clauset , Cristopher Moore

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

Due to the fact that the numbers of annually published papers have witnessed a linear growth in some citation networks, a geometric model is thus proposed to predict some statistical features of those networks, in which the academic…

Physics and Society · Physics 2016-07-07 Qi Liu , Zheng Xie , Engming Dong , Jianping Li

We consider the problem of estimating the parameters in a pairwise graphical model in which the distribution of each node, conditioned on the others, may have a different parametric form. In particular, we assume that each node's…

Methodology · Statistics 2014-08-05 Shizhe Chen , Daniela Witten , Ali Shojaie

For random matrices with tree-like structure there exists a recursive relation for the local Green functions whose solution permits to find directly many important quantities in the limit of infinite matrix dimensions. The purpose of this…

Disordered Systems and Neural Networks · Physics 2015-06-17 E. Bogomolny , O. Giraud

Directed acyclic graphs are the basic representation of the structure underlying Bayesian networks, which represent multivariate probability distributions. In many practical applications, such as the reverse engineering of gene regulatory…

Computation · Statistics 2013-11-15 Jack Kuipers , Giusi Moffa
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