Complex Networks & Their Applications IX -

Complex Networks & Their Applications IX

Volume 2, Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020
Buch | Hardcover
XXVIII, 715 Seiten
2021 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-65350-7 (ISBN)
374,49 inkl. MwSt

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 Classification Using Graph Neural Networks.- Detecting Geographical Competitive Structure for POI Visit Dynamics.- Graph Convolutional Network with Time-based Mini-batch for Information Di usion Prediction.- Experimental Evaluation of Train and Test Split Strategies in Link Prediction.- Incorporating Domain Knowledge into Health Recommender Systems using Hyperbolic Embeddings.- Graph-based Topic Extraction from Vector Embeddings of Text Documents: Application to a Corpus of News Articles.- Topological Analysis of Synthetic Models for Air Transportation Multilayer Networks.- Self-Modeling Networks Using Adaptive Internal Mental Models for Cognitive Analysis and Support Processes.- Extending DeGroot Opinion Formation for Signed Graphs and Minimising Polarization.- Applying Fairness Constraints on Graph Node Ranks Under Personalization Bias.

Erscheinungsdatum
Reihe/Serie Studies in Computational Intelligence
Zusatzinfo XXVIII, 715 p. 216 illus., 183 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 1267 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Graphentheorie
Technik
Schlagworte complex networks • Complex Networks 2020 • network analysis • network dynamics • Network Models
ISBN-10 3-030-65350-1 / 3030653501
ISBN-13 978-3-030-65350-7 / 9783030653507
Zustand Neuware
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