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Complex networks in natural, social, and technological systems generically exhibit an abundance of rich information. Extracting meaningful structural features from data is one of the most challenging tasks in network theory. Many methods…

物理与社会 · 物理学 2012-06-04 Daniel Grady , Christian Thiemann , Dirk Brockmann

Networks are powerful instruments to study complex phenomena, but they become hard to analyze in data that contain noise. Network backbones provide a tool to extract the latent structure from noisy networks by pruning non-salient edges. We…

物理与社会 · 物理学 2017-01-26 Michele Coscia , Frank Neffke

Networks provide useful tools for analyzing diverse complex systems from natural, social, and technological domains. Growing size and variety of data such as more nodes and links and associated weights, directions, and signs can provide…

社会与信息网络 · 计算机科学 2022-03-01 Furkan Gursoy , Bertan Badur

Network analysis is currently used in a myriad of contexts: from identifying potential drug targets to predicting the spread of epidemics and designing vaccination strategies, and from finding friends to uncovering criminal activity.…

数据分析、统计与概率 · 物理学 2010-04-28 R. Guimera , M. Sales-Pardo

A large number of complex systems find a natural abstraction in the form of weighted networks whose nodes represent the elements of the system and the weighted edges identify the presence of an interaction and its relative strength. In…

物理与社会 · 物理学 2009-04-23 M. Angeles Serrano , Marian Boguna , Alessandro Vespignani

Driven by growing interest in the sciences, industry, and among the broader public, a large number of empirical studies have been conducted in recent years of the structure of networks ranging from the internet and the world wide web to…

社会与信息网络 · 计算机科学 2018-06-08 M. E. J. Newman

Most real-world networks are embedded in latent geometries. If a node in a network is found in the vicinity of another node in the latent geometry, the two nodes have a disproportionately high probability of being connected by a link. The…

物理与社会 · 物理学 2024-06-19 Bukyoung Jhun

Networks provide an informative, yet non-redundant description of complex systems only if links represent truly dyadic relationships that cannot be directly traced back to node-specific properties such as size, importance, or coordinates in…

物理与社会 · 物理学 2017-06-12 Valerio Gemmetto , Alessio Cardillo , Diego Garlaschelli

Most empirical studies of networks assume that the network data we are given represent a complete and accurate picture of the nodes and edges in the system of interest, but in real-world situations this is rarely the case. More often the…

社会与信息网络 · 计算机科学 2019-01-02 M. E. J. Newman

Reconstructing weighted networks from partial information is necessary in many important circumstances, e.g. for a correct estimation of systemic risk. It has been shown that, in order to achieve an accurate reconstruction, it is crucial to…

物理与社会 · 物理学 2017-03-07 Tiziano Squartini , Giulio Cimini , Andrea Gabrielli , Diego Garlaschelli

Many algorithms have been proposed to predict missing links in a variety of real networks. These studies focus on mainly both accuracy and efficiency of these algorithms. However, little attention is paid to their robustness against either…

物理与社会 · 物理学 2013-02-26 Liang Wang , Ke Hu , Yi Tang

A fundamental problem in studying and modeling economic and financial systems is represented by privacy issues, which put severe limitations on the amount of accessible information. Here we introduce a novel, highly nontrivial method to…

物理与社会 · 物理学 2018-12-10 Giulio Cimini , Tiziano Squartini , Andrea Gabrielli , Diego Garlaschelli

A major problem in the study of complex socioeconomic systems is represented by privacy issues$-$that can put severe limitations on the amount of accessible information, forcing to build models on the basis of incomplete knowledge. In this…

Structure entails function and thus a structural description of the brain will help to understand its function and may provide insights into many properties of brain systems, from their robustness and recovery from damage, to their dynamics…

神经元与认知 · 定量生物学 2008-08-27 Marcus Kaiser , Robert Martin , Peter Andras , Malcolm P. Young

Network models have been widely used to study diverse systems and analyze their dynamic behaviors. Given the structural variability of networks, an intriguing question arises: Can we infer the type of system represented by a network based…

社会与信息网络 · 计算机科学 2025-05-29 Gonzalo Travieso , Joao Merenda , Odemir M. Bruno

Complex networks are ubiquitous: a cell, the human brain, a group of people and the Internet are all examples of interconnected many-body systems characterized by macroscopic properties that cannot be trivially deduced from those of their…

Despite the huge interest in network resilience to stress, most of the studies have concentrated on internal stress damaging network structure (e.g., node removals). Here we study how networks respond to environmental stress deteriorating…

物理与社会 · 物理学 2018-04-24 Young-Ho Eom

Images of natural systems may represent patterns of network-like structure, which could reveal important information about the topological properties of the underlying subject. However, the image itself does not automatically provide a…

计算机视觉与模式识别 · 计算机科学 2021-09-03 Diego Baptista , Caterina De Bacco

Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical…

统计力学 · 物理学 2016-08-31 Reka Albert , Albert-Laszlo Barabasi

Network science provides effective tools to model and analyze complex systems. However, the increasing size of real-world networks becomes a major hurdle in order to understand their structure and topological features. Therefore, mapping…

社会与信息网络 · 计算机科学 2020-08-11 Zakariya Ghalmane , Chantal Cherifi , Hocine Cherifi , Mohammed El Hassouni
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