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Interactions in many real-world phenomena can be explained by a strong hierarchical structure. Typically, this structure or ranking is not known; instead we only have observed outcomes of the interactions, and the goal is to infer the…

Data Structures and Algorithms · Computer Science 2019-04-24 Nikolaj Tatti

Many real-world phenomena exhibit strong hierarchical structure. Consequently, in many real-world directed social networks vertices do not play equal role. Instead, vertices form a hierarchy such that the edges appear mainly from upper…

Data Structures and Algorithms · Computer Science 2019-02-06 Nikolaj Tatti

Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the…

Social and Information Networks · Computer Science 2017-07-06 Elisa Letizia , Paolo Barucca , Fabrizio Lillo

We present a physics-inspired method for inferring dynamic rankings in directed temporal networks - networks in which each directed and timestamped edge reflects the outcome and timing of a pairwise interaction. The inferred ranking of each…

The entities in directed networks arising from real-world interactions are often naturally organized under some hierarchical structure. Given a directed, weighted, graph with edges and node labels, we introduce ranking problem where the…

Data Structures and Algorithms · Computer Science 2025-02-04 Chamalee Wickrama Arachchi , Nikolaj Tatti

We present a physically-inspired model and an efficient algorithm to infer hierarchical rankings of nodes in directed networks. It assigns real-valued ranks to nodes rather than simply ordinal ranks, and it formalizes the assumption that…

Physics and Society · Physics 2018-06-14 Caterina De Bacco , Daniel B. Larremore , Cristopher Moore

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world…

Physics and Society · Physics 2017-08-30 Hao Liao , Manuel Sebastian Mariani , Matus Medo , Yi-Cheng Zhang , Ming-Yang Zhou

Ranking athletes by their performance in competitions and tournaments is common in every popular sport and has significant benefits that contribute to both the organization and strategic aspects of competitions. Although rankings are…

Physics and Society · Physics 2025-08-28 Bogdán Asztalos , Boldizsár Balázs , Gergely Palla , Tamás Vicsek

Imitation is widely observed in populations of decision-making agents. Using our recent convergence results for asynchronous imitation dynamics on networks, we consider how such networks can be efficiently driven to a desired equilibrium…

Computer Science and Game Theory · Computer Science 2017-04-17 James Riehl , Pouria Ramazi , Ming Cao

A highly successful approach to route planning in networks (particularly road networks) is to identify a hierarchy in the network that allows faster queries after some preprocessing that basically inserts additional "shortcut"-edges into a…

Data Structures and Algorithms · Computer Science 2019-09-11 Demian Hespe , Peter Sanders

The importance of a node in a directed graph can be measured by its PageRank. The PageRank of a node is used in a number of application contexts - including ranking websites - and can be interpreted as the average portion of time spent at…

Data Structures and Algorithms · Computer Science 2014-05-22 Balázs Csanád Csáji , Raphaël M. Jungers , Vincent D. Blondel

Dynamic networks are graphs in which edges are available only at specific time instants, modeling connections that change over time. The dynamic network creation game studies this setting as a strategic interaction where each vertex…

Data Structures and Algorithms · Computer Science 2026-03-17 Binh-Minh Bui-Xuan , Nhat-Minh Nguyen , Sébastien Tixeuil , Yukiko Yamauchi

Temporal networks model a variety of important phenomena involving timed interactions between entities. Existing methods for machine learning on temporal networks generally exhibit at least one of two limitations. First, time is assumed to…

Machine Learning · Computer Science 2022-10-04 Sudhanshu Chanpuriya , Ryan A. Rossi , Sungchul Kim , Tong Yu , Jane Hoffswell , Nedim Lipka , Shunan Guo , Cameron Musco

Temporal graphs (in which edges are active at specified times) are of particular relevance for spreading processes on graphs, e.g.~the spread of disease or dissemination of information. Motivated by real-world applications, modification of…

Computational Complexity · Computer Science 2022-12-22 Jessica Enright , Kitty Meeks , Fiona Skerman

Many real world networks are considered temporal networks, in which the chronological ordering of the edges has importance to the meaning of the data. Performing temporal subgraph matching on such graphs requires the edges in the subgraphs…

Data Structures and Algorithms · Computer Science 2018-01-25 Patrick Mackey , Katherine Porterfield , Erin Fitzhenry , Sutanay Choudhury , George Chin

Dynamic networks have intrinsic structural, computational, and multidisciplinary advantages. Link prediction estimates the next relationship in dynamic networks. However, in the current link prediction approaches, only bipartite or…

Social and Information Networks · Computer Science 2020-06-09 Mohamoud Ali , Yugyung Lee , Praveen Rao

Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the…

Physics and Society · Physics 2019-01-09 Seungkyu Shin , Sebastian E. Ahnert , Juyong Park

We consider the prisoner's dilemma being played repeatedly on a dynamic network, where agents may choose their actions as well as their co-players. This leads to co-evolution of network structure and strategy patterns of the players.…

Physics and Society · Physics 2007-06-26 Christoly Biely , Klaus Dragosits , Stefan Thurner

We describe a novel method for modeling non-stationary multivariate time series, with time-varying conditional dependencies represented through dynamic networks. Our proposed approach combines traditional multi-scale modeling and network…

Methodology · Statistics 2017-12-25 Xinyu Kang , Apratim Ganguly , Eric D. Kolaczyk

From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based…

Physics and Society · Physics 2012-12-07 Shun Motegi , Naoki Masuda
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