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Complex Networks & Their Applications IX: Volume 1, Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020 2021 ed. [Kietas viršelis]

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  • Formatas: Hardback, 685 pages, aukštis x plotis: 235x155 mm, weight: 1232 g, 207 Illustrations, color; 30 Illustrations, black and white; XXVII, 685 p. 237 illus., 207 illus. in color., 1 Hardback
  • Serija: Studies in Computational Intelligence 943
  • Išleidimo metai: 20-Dec-2020
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030653463
  • ISBN-13: 9783030653460
Kitos knygos pagal šią temą:
Complex Networks & Their Applications IX: Volume 1, Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020 2021 ed.Didesnis paveikslėlis
  • Formatas: Hardback, 685 pages, aukštis x plotis: 235x155 mm, weight: 1232 g, 207 Illustrations, color; 30 Illustrations, black and white; XXVII, 685 p. 237 illus., 207 illus. in color., 1 Hardback
  • Serija: Studies in Computational Intelligence 943
  • Išleidimo metai: 20-Dec-2020
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030653463
  • ISBN-13: 9783030653460
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9783030653460.html

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the IX International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks and technological networks. 

 


Structural Node Embedding in Signed Social Networks: Finding Online
Misbehavior at Multiple Scales.- On the Impact of Communities on
Semi-supervised Classication Using Graph Neural Networks.- Detecting
Geographical Competitive Structure for POI Visit Dynamics.- Graph
Convolutional Network with Time-based Mini-batch for Information Diusion
Prediction.- Experimental Evaluation of Train and Test Split Strategies in
Link Prediction.- Incorporating Domain Knowledge into Health Recommender
Systems Using Hyperbolic Embeddings.- Learning Parameters for Balanced Index
Inuence Maximization.- Connecting the Dots: Integrating Point Location Data
into Spatial Network Analyses.- Topological Analysis of Synthetic Models for
Air Transportation Multilayer Networks.- Extending DeGroot Opinion Formation
for Signed Graphs and Minimising Polarization.- Forming Diverse Teams Based
on Members Social Networks: A Genetic Algorithm Approach.