Buch, Englisch, Band 943, 685 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1066 g
Volume 1, Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020
Buch, Englisch, Band 943, 685 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1066 g
Reihe: Studies in Computational Intelligence
ISBN: 978-3-030-65349-1
Verlag: Springer International Publishing
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Structural Node Embedding in Signed Social Networks: Finding Online Misbehavior at Multiple Scales.- On the Impact of Communities on Semi-supervised Classi?cation 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.- Learning Parameters for Balanced Index In?uence 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.
