Computation in Complex Networks

doi:10.3390/books978-3-0365-0683-8

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Computation in Complex Networks

Edited by

August 2021

352 pages

ISBN978-3-0365-0682-1 (Hardback)
ISBN978-3-0365-0683-8 (PDF)

https://doi.org/10.3390/books978-3-0365-0683-8

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This book is a reprint of the Special Issue Computation in Complex Networks that was published in

Chemistry & Materials Science

Computer Science & Mathematics

Physical Sciences

Summary

Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine

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Hardback

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Keywords

city interaction network; evolution model; preferential attachment; WeChat; maximum likelihood; chimera states; coupled map lattice; nilpotent matrix; community detection; membrane algorithm; self-organizing map network; complex networks; optimization; structural balance; minimum memory based sign adjustment; social networks; NW network; convergence; complex system simulation; cloud computing architecture; service-oriented modeling; semantic search framework; QoS-based service selection; complex networks; cascading failures; network topology; null models; SciSci; knowledge evolution; machine learning; bridging centrality; community detection; disjoint nodes; disjunct nodes; node similarity; overlapping nodes; Bayesian networks; entropy; socio-ecological system; complex network; chaotic time series; Gaussian mixture model; maximum mean discrepancy; complex networks; angiogenesis; network properties; variational inference; graph neural network; variational autoencoder; network embedding; online social networks; social media; information spreading; information diffusion; cross-entropy; cross-domain recommendation; sentiment analysis; latent sentiment review feature; non-linear mapping; dissimilarity spaces; support vector machines; kernel methods; computational biology; systems biology; protein contact networks; data mining; community detection; overlapping communities; modularity; complex networks; literary works; genre classification; stylistic attributes; lemmatization; renormalisation process; network growth; preferential attachment; inverse preferential attachment; language networks; language development; multilayer complex networks; stability; spreading control; machine learning; graph neural networks; node classification; active learning; graph representation learning; n/a