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Complex Networks XV Proceedings of the 15th Conference on Complex Networks, CompleNet 2024 /

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 i...

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Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Botta, Federico (Επιμελητής έκδοσης), Macedo, Mariana (Επιμελητής έκδοσης), Barbosa, Hugo (Επιμελητής έκδοσης), Menezes, Ronaldo (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:Αγγλικά
Έκδοση: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Έκδοση:1st ed. 2024.
Σειρά:Springer Proceedings in Complexity,
Θέματα:
Graph theory.
Sociology > Methodology.
System theory.
Computational intelligence.
Graph Theory.
Sociological Methods.
Complex Systems.
Computational Intelligence.
Διαθέσιμο Online:https://doi.org/10.1007/978-3-031-57515-0
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Πίνακας περιεχομένων:
  • 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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