Titlebook: Complex Networks & Their Applications XII; Proceedings of The T Hocine Cherifi,Luis M. Rocha,Murat Donduran Conference proceedings 2024 The

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书目名称Complex Networks & Their Applications XII影响因子(影响力)




书目名称Complex Networks & Their Applications XII影响因子(影响力)学科排名




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书目名称Complex Networks & Their Applications XII被引频次学科排名




书目名称Complex Networks & Their Applications XII年度引用




书目名称Complex Networks & Their Applications XII年度引用学科排名




书目名称Complex Networks & Their Applications XII读者反馈




书目名称Complex Networks & Their Applications XII读者反馈学科排名

大吃大喝

Bayesian Hierarchical Network Autocorrelation Models for Modeling the Diffusion of Hospital-Level Quto as social influence or contagion) is believed to act between units (e.g., hospitals) above the level at which data is observed. We develop two hierarchical network autocorrelation models to represent peer effects between hospitals when modeling individual outcomes of the patients who attend those

Basilar-Artery

Foreshadow

Does Isolating High-Modularity Communities Prevent Cascading Failure?y partitions. It seems obvious that isolating high-modularity communities is a good way to prevent the spread of cascading failures. Here we develop a heuristic approach informed by Moore-Shannon network reliability that focuses on dynamics rather than topology. It defines communities directly in te

嫌恶

Two to Five Truths in Non-negative Matrix Factorizationent a scaling inspired by the normalized Laplacian (NL) for graphs that can greatly improve the quality of a non-negative matrix factorization. The results parallel those in the spectral graph clustering work of [.], where the authors proved adjacency spectral embedding (ASE) spectral clustering was

LATHE

LATHE

Exclude

Dual Communities Characterize Structural Patterns and Robustness in Leaf Venation Networks analysis can be complemented by the definition of communities in the networks’ plane dual. Such communities are characterized not by weak but by strong connectivity between the different components of the network. We extract dual communities in leaf venation networks, finding that they can reveal s

试验

Tailoring Benchmark Graphs to Real-World Networks for Improved Prediction of Community Detection Per algorithm and trust the generated results without further investigation, but algorithm performance can vary depending on the network characteristics. We demonstrate that by running experiments on benchmark graphs tailored to match characteristics of a real-world network of interest, a better unders

attenuate

Network Based Methodology for Characterizing Interdisciplinary Expertise in Emerging Research-world problems. Understanding characteristics of IDR early (as soon as projects get funded), can formatively shape a research community at portfolio, project, and individual investigator levels. This involves surfacing the interacting components and the context that manifest IDR. We present a netwo