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Confining an answer to the question whether and how the coherent operation of network elements is determined by the the network structure is the topic of our work. We map the structure of signal flow in directed networks by analysing the…

Data Analysis, Statistics and Probability · Physics 2011-06-22 M. Bányai , L. Négyessy , F. Bazsó

Standard agglomerative clustering suggests establishing a new reliable linkage at every step. However, in order to provide adaptive, density-consistent and flexible solutions, we study extracting all the reliable linkages at each step,…

Machine Learning · Computer Science 2023-01-02 Morteza Haghir Chehreghani

Correlation clustering is a widely-used approach for clustering large data sets based only on pairwise similarity information. In recent years, there has been a steady stream of better and better classical algorithms for approximating this…

Data Structures and Algorithms · Computer Science 2025-04-08 Sepehr Assadi , Sanjeev Khanna , Aaron Putterman

Real social networks are often compared to random graphs in order to assess whether their typological structure could be the result of random processes. However, an Erd\H{o}s-R\'enyi random graph in large scale is often lack of local…

Physics and Society · Physics 2013-01-30 Cheng Wang

Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each…

Statistical Mechanics · Physics 2017-04-07 Emilio Flores-Sola , Martin Weigel , Ralph Kenna , Bertrand Berche

Although many successful ensemble clustering approaches have been developed in recent years, there are still two limitations to most of the existing approaches. First, they mostly overlook the issue of uncertain links, which may mislead the…

Machine Learning · Statistics 2016-06-06 Dong Huang , Jian-Huang Lai , Chang-Dong Wang

We develop a full theoretical approach to clustering in complex networks. A key concept is introduced, the edge multiplicity, that measures the number of triangles passing through an edge. This quantity extends the clustering coefficient in…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. Angeles Serrano , Marian Boguna

We propose a simple growing model for the evolution of small-world networks. It is introduced as a modified BA model in which all the edges connected to the new nodes are made locally to the creator and its nearest neighbors. It is found…

Mathematical Physics · Physics 2009-11-13 Xinping Xu , Feng Liu , Wei Li

Aiming to understand real-world hierarchical networks whose degree distributions are neither power law nor exponential, we construct a hybrid clique network that includes both homogeneous and inhomogeneous parts, and introduce an…

Social and Information Networks · Computer Science 2015-06-18 Yimin Ding , Bin Zhou , Xiaosong Chen

We define a hierarchical clustering method: $\alpha$-unchaining single linkage or $SL(\alpha)$. The input of this algorithm is a finite metric space and a certain parameter $\alpha$. This method is sensitive to the density of the…

Machine Learning · Computer Science 2014-02-07 Álvaro Martínez-Pérez

The percolation properties of clustered networks are analyzed in detail. In the case of weak clustering, we present an analytical approach that allows to find the critical threshold and the size of the giant component. Numerical simulations…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. Angeles Serrano , Marian Boguna

We study the statistical properties of the sampled networks by a random walker. We compare topological properties of the sampled networks such as degree distribution, degree-degree correlation, and clustering coefficient with those of the…

Physics and Society · Physics 2009-11-13 Sooyeon Yoon , Sungmin Lee , Soon-Hyung Yook , Yup Kim

Until recently obtaining data on populations of networks was typically rare. However, with the advancement of automatic monitoring devices and the growing social and scientific interest in networks, such data has become more widely…

Methodology · Statistics 2020-01-22 Mirko Signorelli , Ernst Wit

Data clustering, the task of grouping observations according to their similarity, is a key component of unsupervised learning -- with real world applications in diverse fields such as biology, medicine, and social science. Often in these…

Machine Learning · Computer Science 2023-09-20 Anne Sophie Riis Damstrup , Sofie Tosti Madsen , Michele Coscia

With complex networks emerging as an effective tool to tackle multidisciplinary problems, models of network generation have gained an importance of their own. These models allow us to extensively analyze the data obtained from real-world…

Physics and Society · Physics 2018-09-05 G. Kashyap , G. Ambika

Recently there have been a tremendous interest in models of networks with a power-law distribution of degree -- so called "scale-free networks." It has been observed that such networks, normally, have extremely short path-lengths, scaling…

Disordered Systems and Neural Networks · Physics 2007-05-23 Petter Holme

Finding structural similarities in graph data, like social networks, is a far-ranging task in data mining and knowledge discovery. A (conceptually) simple reduction would be to compute the automorphism group of a graph. However, this…

Social and Information Networks · Computer Science 2020-02-28 Stephan Doerfel , Tom Hanika , Gerd Stumme

Real-world networks, e.g. the social relations or world-wide-web graphs, exhibit both small-world and scale-free behaviour. We interpret lattice triangulations as planar graphs by identifying triangulation vertices with graph nodes and…

Disordered Systems and Neural Networks · Physics 2015-02-06 Benedikt Krüger , Ella M. Schmidt , Klaus Mecke

Hierarchical crack patterns that arise during the drying of thin films of colloidal dispersions or polymer solutions on a solid substrate are of interest both from a fundamental standpoint and in the context of the creation of transparent…

Disordered Systems and Neural Networks · Physics 2026-03-26 Yuri Yu. Tarasevich , Andrei V. Eserkepov , Andrei S. Burmistrov

Clustering, or transitivity has been observed in real networks and its effects on their structure and function has been discussed extensively. The focus of these studies has been on clustering of single networks while the effect of…

Physics and Society · Physics 2015-06-16 Shuai Shao , Xuqing Huang , H. Eugene Stanley , Shlomo Havlin