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Algorithms and Models for the Web Graph

Overview of attention for book
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 5: Assortativity and Bidegree Distributions on Bernoulli Random Graph Superpositions
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mendeley
2 Mendeley
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Chapter title
Assortativity and Bidegree Distributions on Bernoulli Random Graph Superpositions
Chapter number 5
Book title
Algorithms and Models for the Web Graph
Published by
Springer, Cham, September 2020
DOI 10.1007/978-3-030-48478-1_5
Book ISBNs
978-3-03-048477-4, 978-3-03-048478-1
Authors

Mindaugas Bloznelis, Joona Karjalainen, Lasse Leskelä, Bloznelis, Mindaugas, Karjalainen, Joona, Leskelä, Lasse

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Librarian 1 50%
Lecturer > Senior Lecturer 1 50%
Readers by discipline Count As %
Computer Science 2 100%

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