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Complex Networks XV Proceedings of the 15th Conference on Complex Networks, CompleNet 2024
Title
Complex Networks XV [electronic resource] : Proceedings of the 15th Conference on Complex Networks, CompleNet 2024 / edited by Federico Botta, Mariana Macedo, Hugo Barbosa, Ronaldo Menezes.
ISBN
9783031575150
Edition
1st ed. 2024.
Publication
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Physical Description
1 online resource (XII, 218 p.) 77 illus., 72 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
The International Conference on Complex Networks (CompleNet) brings together researchers and practitioners from diverse disciplines working on areas related to complex networks. CompleNet has been an active conference since 2009. Over the past two decades, we have witnessed an exponential increase in the number of publications and research centres dedicated to this field of Complex Networks (aka Network Science). From biological systems to computer science, from technical to informational networks, and from economic to social systems, complex networks are becoming pervasive for dozens of applications. It is the interdisciplinary nature of complex networks that CompleNet aims to capture and celebrate. The CompleNet conference is one of the most cherished events by scientists in our field. Maybe it is because of its motivating format, consisting of plenary sessions (no parallel sessions); or perhaps the reason is that it finds the perfect balance between young and senior participation, a balance in the demographics of the presenters, or perhaps it is just the quality of the work presented.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
May 08, 2024
Series
Springer Proceedings in Complexity,
Contents
Chapter 1: Mapping low-resolution edges to high-resolution paths: the case of traffic measurements in cities
Chapter 2: From Low Resource Information Extraction to Identifying Influential Nodes in Knowledge Graphs
Chapter 3: Inhomogenous Marketing Mix Diffusion
Chapter 4: Modelling both pairwise interactions and group effects in polarization on interaction networks
Chapter 5: Computing Motifs in Hypergraphs
Chapter 6: Extending network tools to explore trends in temporal granular trade networks
Chapter 7: Expressivity of Geometric Inhomogeneous Random Graphs-Metric and Non-Metric
Chapter 8: Social Interactions Matter: Is Grey Wolf Optimizer a Particle Swarm Optimization Variation?
Chapter 9: Exploring Ingredient Variability in Classic Russian Cuisine Dishes through Complex Network Analysis
Chapter 10: Unraveling the Structure of Knowledge: Consistency in Everyday Networks, Diversity in Scientific
Chapter 11: Kinetic-based force-directed graph embedding
Chapter12: Deep Graph Machine Learning Models for Epidemic Spread Prediction and Prevention
Chapter 13: EleMi: A robust method to infer soil ecological networks with better community structure
Chapter 14: Interpreting Node Embedding Distances Through n-order Proximity Neighbourhoods
Chapter 15: Edge Dismantling with Geometric Reinforcement Learning
Chapter 16: Public Transit Inequality in the Context of the Built Environment.
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