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Finding key players in complex networks

WebJun 26, 2024 · FINDER, which stands for FInding key players in Networks through DEep Reinforcement learning, builds on recently developed deep learning techniques for solving combinatorial optimization … WebJan 13, 2024 · Influence maximization (IM) in complex networks tries to activate a small subset of seed nodes that could maximize the propagation of influence. The studies on IM have attracted much attention due to their wide applications such as item recommendation, viral marketing, information propagation and disease immunization. Existing works …

Finding Influencers in Complex Networks: A Novel Method Based …

WebMay 1, 2024 · The model identified 23 new (manually verified) HIV-related influencers, including health and research organizations and local HIV advocates across the United States. Our proposed model achieved the highest accuracy/recall, with an average improvement of 38.5% over the other baseline models. Conclusion: WebOct 17, 2024 · Finding key players in complex networks through deep reinforcement learning. Nature machine intelligence, Vol. 2, 6 (2024), 317--324. Linton C Freeman. 1977. A Set of Measures of Centrality Based on Betweenness. Sociometry, Vol. 40, 1 (1977), 35--41. Felipe Grando, Lisandro Z. Granville, and Luis C. Lamb. 2024. beau massage https://maskitas.net

Finding key players in complex networks through deep …

WebFinding an optimal set of nodes, called key players, whose activation (or removal) would maximally enhance (or degrade) a certain network functionality, is a fundamental class … WebAug 1, 2024 · Finding key players in complex networks through deep reinforcement learning. Nat. Mach. Intell. (2024) ... To find the important nodes in complex networks is a fundamental issue. A number of methods have been recently proposed to address this problem but most previous studies have the limitations, and few of them considering both … WebMay 21, 2024 · Finding key players in complex networks through deep reinforcement learning Article Full-text available Jun 2024 Changjun Fan Zeng li Yizhou Sun Yang-Yu Liu View Show abstract Revisiting the... dijera sinonimo

Disintegrating spatial networks based on region centrality

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Finding key players in complex networks

A deep reinforcement learning framework to identify key …

WebIn recent years, some works are proposed to find key nodes via network connectivity measures, these studies assume a static environment, and besides, key nodes are calculated through pairwise connectivity, the number of connected components and other measures from the perspective of graph theory. ... Yang-Yu Liu, Finding key players in … WebFinding key players in complex networks through deep reinforcement learning. Authors: Fan, Changjun; Zeng, Li; Sun, Yizhou; Liu, Yang-Yu. Award ID (s): 1705169 1741634. …

Finding key players in complex networks

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WebOct 26, 2024 · According to the results, our proposed method outperforms classical methods in identifying influential nodes and also indicates the potential for analyzing the influence evolution of networks, which shows a positive and effective impact on locating influencers and predicting potential key players in the future. WebOct 26, 2024 · Finding Influencers in Complex Networks: A Novel Method Based on Information Theory October 2024 PP (99):1-9 10.1109/JSYST.2024.3119081 Authors: …

WebNov 12, 2024 · Network science plays an extremely key role in many fields 1. The heterogeneity of real networks 2 puts forward a vital question: How to measure the … WebFeb 6, 2024 · In complex networks, understanding of the dynamics of the information spread in the networks is a crucial task in various ... Zeng, L.; Sun, Y.; Liu, Y.-Y.: Finding key players in complex networks through deep reinforcement learning. Nature Mach. Intell. 2, 317–324 (2024) Article Google Scholar Freeman, L.C.: Centrality in social …

WebAs we focus on both the efficiency and accuracy of the algorithm, three centralities with low computational complexity are introduced: the sum of neighbors’ degree, the number of communities a node is connected with, and the k-core value. WebOct 26, 2024 · Finding Influencers in Complex Networks: A Novel Method Based on Information Theory October 2024 PP (99):1-9 10.1109/JSYST.2024.3119081 Authors: Yanli Hu Jichao Li Yirun Ruan Abstract Key...

WebJun 1, 2024 · Finding an optimal set of nodes, called key players, whose activation (or removal) would maximally enhance (or degrade) a certain …

WebDec 13, 2024 · Identifying the influential nodes in complex networks plays a crucial role in the fields of epidemic control and public opinion guidance. ... Fan C, Zeng L, Sun Y, (2024). Finding key players in complex networks through deep reinforcement learning. Nature machine intelligence 2(6), 317-324. Google Scholar; Liu D, Jing Y, Zhao J, (2024). A fast ... dijera o dijiera raeWebDec 1, 2024 · In this section, we first present the sequential-path trees, a new presentation structure of temporal networks in detail. Then, we introduce how to extract the three temporal features, i.e., propagation time, hop count, and reachable paths. beau mastersonWebIdentifying key players in coupled individual systems is a fundamental problem in network theory. We investigate synchronizable network-coupled dynamical systems such as high … dijeramos