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Algorithms and Models for the Web Graph

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Cover of 'Algorithms and Models for the Web Graph'

Table of Contents

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    Book Overview
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    Chapter 1 Hypergraph Analytics of Domain Name System Relationships
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    Chapter 2 Global Graph Curvature
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    Chapter 3 Information Diffusion in Complex Networks: A Model Based on Hypergraphs and Its Analysis
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    Chapter 4 A Scalable Unsupervised Framework for Comparing Graph Embeddings
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    Chapter 5 Assortativity and Bidegree Distributions on Bernoulli Random Graph Superpositions
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    Chapter 6 Clustering Coefficient of a Preferred Attachment Affiliation Network
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    Chapter 7 Transience Versus Recurrence for Scale-Free Spatial Networks
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    Chapter 8 The Iterated Local Directed Transitivity Model for Social Networks
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    Chapter 9 A Note on the Conductance of the Binomial Random Intersection Graph
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    Chapter 10 Iterated Global Models for Complex Networks
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    Chapter 11 A Robust Method for Statistical Testing of Empirical Power-Law Distributions
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    Chapter 12 Community Structures in Information Networks for a Discrete Agent Population
Attention for Chapter 7: Transience Versus Recurrence for Scale-Free Spatial Networks
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Summary
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Chapter title
Transience Versus Recurrence for Scale-Free Spatial Networks
Chapter number 7
Book title
Algorithms and Models for the Web Graph
Published by
Springer, Cham, September 2020
DOI 10.1007/978-3-030-48478-1_7
Book ISBNs
978-3-03-048477-4, 978-3-03-048478-1
Authors

Peter Gracar, Markus Heydenreich, Christian Mönch, Peter Mörters, Gracar, Peter, Heydenreich, Markus, Mönch, Christian, Mörters, Peter

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