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Complex networks IX : proceedings of the 9th Conference on Complex Networks CompleNet 2018

Author: Sean Cornelius
Publisher: Cham, Switzerland : Springer, [2018] ©2018
Series: Springer proceedings in complexity.; Springer complexity.
Edition/Format:   eBook : Document : Conference publication : EnglishView all editions and formats
Summary:
This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) 2018 in Boston, MA in March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of  Read more...
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Genre/Form: Electronic books
Conference papers and proceedings
Congresses
Additional Physical Format: Printed edition:
Material Type: Conference publication, Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Sean Cornelius
ISBN: 9783319731988 331973198X
OCLC Number: 1023575360
Description: 1 online resource
Contents: Intro; Preface; Contents; Contributors; Theory of Complex Networks; On the Eccentricity Function in Graphs; 1 Introduction; 2 Eccentricity, Locality, and Monotonicity; 3 Unimodality of the Eccentricity Function and the Center; 4 Experiments on Real-World Networks; 5 Concluding Remarks; References; Density Decompositions of Networks; 1 Introduction; 1.1 Related Work; 2 The Density Decomposition; 2.1 Density and the Density Decomposition; 2.2 Interpretation of Density Rank; 2.3 Relationship to k-Cores; 3 The Similarity of Degree and Density Distributions. 3.1 The Dissimilarity of Degree and Density Distributions of Random Networks4 Conclusion; References; Fast Streaming Small Graph Canonization; 1 Introduction; 2 Preliminaries; 2.1 Problem Definition; 3 Proposed Method; 3.1 The Automaton; 3.2 Building the Automaton; 4 Analysis; 4.1 Theoretical Analysis; 4.2 Empirical Analysis; 4.3 Case Study; 5 Conclusion; References; Silhouette for the Evaluation of Community Structures in Multiplex Networks; 1 Introduction; 2 Related Work; 3 Multiplex Silhouette; 4 Evaluation Methodology; 5 Results; 6 Conclusion; References. Jaccard Curvatureâ#x80;#x94;an Efficient Proxy for Ollivier-Ricci Curvature in Graphs1 Introduction; 2 Curvature Metrics; 3 Theoretical Results; 4 Experimental Results; 4.1 Network Models; 4.2 Real-World Networks; 5 Conclusion; References; Combinatorial Millerâ#x80;#x93;Hagberg Algorithm for Randomization of Dense Networks; 1 Introduction; 2 Revising the MH Algorithm with Combinatorial Edge Probability; 3 Evaluations; 4 Conclusions; References; Proposal of Strategic Link Addition for Improving the Robustness of Multiplex Networks; 1 Introduction; 2 Related Work; 3 Link Addition Strategy. 3.1 Link Addition Strategies Using IDD3.2 Link Addition Strategies Using IDD and Degree of Layer Node; 4 Methodology; 4.1 Overview; 4.2 Generating Duplex Network; 4.3 Network Attack Simulation; 5 Results and Discussion; 6 Conclusion and Future Works; References; Graph Embeddings; Embedding-Centrality: Generic Centrality Computation Using Neural Networks; 1 Introduction; 2 Background; 3 Embedding Centrality; 3.1 Complexity; 3.2 Discussion; 4 Evaluation; 5 Conclusions; References; Fast Sequence-Based Embedding with Diffusion Graphs; 1 Introduction; 2 Related Works. 3 Feature Extraction and Neural Network Embedding4 Sequence Generation Algorithm and Design; 5 Experiments; 6 Conclusions; References; Semi-supervised Graph Embedding Approach to Dynamic Link Prediction; 1 Introduction; 2 Proposed Method; 2.1 Notations; 2.2 Learning from Past Formation and Dissolution Networks; 2.3 Graph Embedding from the Current Network; 2.4 Semi-supervised Graph Embedding Approach; 2.5 Prediction; 3 Training; 4 Experiments; 4.1 Data; 4.2 Evaluation Criteria; 4.3 Baseline Methods; 4.4 Experimental Results; 5 Conclusions; References.
Series Title: Springer proceedings in complexity.; Springer complexity.
Other Titles: Complex networks 9
Responsibility: Sean Cornelius [and four others] editors.

Abstract:

This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks.  Read more...

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