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The concept of k-core in complex networks plays a key role in many applications, e.g., understanding the global structure, or identifying central/critical nodes, of a network. A malicious attacker with jamming ability can exploit the…

Social and Information Networks · Computer Science 2021-12-01 Bo Zhou , Yuqian Lv , Jinhuan Wang , Jian Zhang , Qi Xuan

A visualisation tool is presented to facilitate the study on large-scale communications networks. This tool provides a simple and effective way to summarise the topology of a complex network at a coarse level.

Networking and Internet Architecture · Computer Science 2009-09-29 Yuchun Guo , Changjia Chen , Shi Zhou

Core-periphery structure, the arrangement of a network into a dense core and sparse periphery, is a versatile descriptor of various social, biological, and technological networks. In practice, different core-periphery algorithms are often…

Social and Information Networks · Computer Science 2021-04-23 Ryan J. Gallagher , Jean-Gabriel Young , Brooke Foucault Welles

Going beyond networks, to include higher-order interactions of arbitrary sizes, is a major step to better describe complex systems. In the resulting hypergraph representation, tools to identify structures and central nodes are scarce. We…

Physics and Society · Physics 2023-10-11 Marco Mancastroppa , Iacopo Iacopini , Giovanni Petri , Alain Barrat

A key graph mining primitive is extracting dense structures from graphs, and this has led to interesting notions such as $k$-cores which subsequently have been employed as building blocks for capturing the structure of complex networks and…

Social and Information Networks · Computer Science 2022-08-25 Farnoosh Hashemi , Ali Behrouz , Laks V. S. Lakshmanan

The k-truss model is one of the most important models in cohesive subgraph analysis. The k-truss decomposition problem is to compute the trussness of each edge in a given graph, and has been extensively studied. However, the conventional…

Data Structures and Algorithms · Computer Science 2024-11-12 Chen Chen , Jingya Qian , Hui Luo , Yongye Li , Xiaoyang Wang

We propose a method for characterizing large complex networks by introducing a new matrix structure, unique for a given network, which encodes structural information; provides useful visualization, even for very large networks; and allows…

Disordered Systems and Neural Networks · Physics 2008-02-28 J. P. Bagrow , E. M. Bollt , J. D. Skufca , D. ben-Avraham

The discovery of small world and scale free properties of many real world networks has revolutionized the way we study, analyze, model and process networks. An important way to analyze these complex networks is to visualize them using graph…

Social and Information Networks · Computer Science 2023-04-05 Faraz Zaidi

In this paper, we investigate the parallelization of $k$-core decomposition, a method used in graph analysis to identify cohesive substructures and assess node centrality. Although efficient sequential algorithms exist for this task, the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-02 Davide Rucci , Sebastian Parfeniuc , Matteo Mordacchini , Emanuele Carlini , Alfredo Cuzzocrea , Patrizio Dazzi

Networks are a natural and popular mechanism for the representation and investigation of a broad class of systems. But extracting information from a network can present significant challenges. We present NetzCope, a software application for…

Data Analysis, Statistics and Probability · Physics 2017-08-23 Michael J. Barber , Ludwig Streit , Oleg Strogan

Many networks can be usefully decomposed into a dense core plus an outlying, loosely-connected periphery. Here we propose an algorithm for performing such a decomposition on empirical network data using methods of statistical inference. Our…

Social and Information Networks · Computer Science 2015-06-22 Xiao Zhang , Travis Martin , M. E. J. Newman

The k-core decomposition of a network has thus far mainly served as a powerful tool for the empirical study of complex networks. We now propose its explicit integration in a theoretical model. We introduce a Hard-core Random Network model…

Physics and Society · Physics 2014-02-11 Laurent Hébert-Dufresne , Antoine Allard , Jean-Gabriel Young , Louis J. Dubé

Large networks are useful in a wide range of applications. Sometimes problem instances are composed of billions of entities. Decomposing and analyzing these structures helps us gain new insights about our surroundings. Even if the final…

Core decomposition is a fundamental graph problem with a large number of applications. Most existing approaches for core decomposition assume that the graph is kept in memory of a machine. Nevertheless, many real-world graphs are big and…

Databases · Computer Science 2015-11-03 Dong Wen , Lu Qin , Ying Zhang , Xuemin Lin , Jeffrey Xu Yu

Networks (or graphs) are used to model the dyadic relations between entities in a complex system. In cases where there exists multiple relations between the entities, the complex system can be represented as a multilayer network, where the…

Social and Information Networks · Computer Science 2019-10-04 Abhishek Santra , Sanjukta Bhowmick , Sharma Chakravarthy

Massive network exploration is an important research direction with many applications. In such a setting, the network is, usually, modeled as a graph $G$, whereas any structural information of interest is extracted by inspecting the way…

Data Structures and Algorithms · Computer Science 2017-12-11 Panagiotis Strouthopoulos , Apostolos Papadopoulos

In complex networks, many elements interact with each other in different ways. A hypergraph is a network in which group interactions occur among more than two elements. In this study, first, we propose a method to identify influential…

Statistical Mechanics · Physics 2023-06-29 Jongshin Lee , Kwang-Il Goh , Deok-Sun Lee , B. Kahng

Internet is a complex network composed by several networks: the Autonomous Systems, each one designed to transport information efficiently. Routing protocols aim to find paths between nodes whenever it is possible (i.e., the network is not…

Discrete Mathematics · Computer Science 2012-02-21 José Ignacio Alvarez-Hamelin , Beiró Mariano Gastón , Jorge Rodolfo Busch

Visualizing high-dimensional data has been a focus in data analysis communities for decades, which has led to the design of many algorithms, some of which are now considered references (such as t-SNE for example). In our era of overwhelming…

Machine Learning · Computer Science 2017-02-21 Johan Paratte , Nathanaël Perraudin , Pierre Vandergheynst

Graph decompositions are the natural generalisation of tree decompositions where the decomposition tree is replaced by a genuine graph. Recently they found theoretical applications in the theory of sparsity, topological graph theory,…

Discrete Mathematics · Computer Science 2023-12-20 Johannes Carmesin , Sarah Frenkel