Computation in Complex Networks

• Muut tekijät: Pizzuti, Clara (Toimittaja), Socievole, Annalisa (Toimittaja)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Aiheet: Technology: general issues; 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; cascading failures; network topology; null models; SciSci; knowledge evolution; machine learning; bridging centrality; 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; 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; overlapping communities; modularity; literary works; genre classification; stylistic attributes; lemmatization; renormalisation process; network growth; inverse preferential attachment; language networks; language development; multilayer complex networks; stability; spreading control; graph neural networks; node classification; active learning; graph representation learning; n/a
• Linkit: DOAB: download the publication; DOAB: description of the publication

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, su...