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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 Asymmetric Distribution of Nodes in the Spatial Preferred Attachment Model
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    Chapter 2 A Spatial Preferential Attachment Model with Local Clustering
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    Chapter 3 A Local Clustering Algorithm for Connection Graphs
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    Chapter 4 On the Power of Adversarial Infections in Networks
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    Chapter 5 On the Choice of Kernel and Labelled Data in Semi-supervised Learning Methods
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    Chapter 6 A Nearly-Sublinear Method for Approximating a Column of the Matrix Exponential for Matrices from Large, Sparse Networks
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    Chapter 7 Evolution of the Media Web
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    Chapter 8 Random Intersection Graph Process
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    Chapter 9 Alpha Current Flow Betweenness Centrality
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    Chapter 10 Tree Nash Equilibria in the Network Creation Game
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    Chapter 11 Fast Low-Cost Estimation of Network Properties Using Random Walks
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    Chapter 12 An L p Norm Relaxation Approach to Positive Influence Maximization in Social Network under the Deterministic Linear Threshold Model
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    Chapter 13 Fast Algorithms for the Maximum Clique Problem on Massive Sparse Graphs
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    Chapter 14 A Faster Algorithm to Update Betweenness Centrality after Node Alteration
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    Chapter 15 Generalized Preferential Attachment: Tunable Power-Law Degree Distribution and Clustering Coefficient
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    Chapter 16 Solving Linear Systems with Boundary Conditions Using Heat Kernel Pagerank
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    Chapter 17 Anarchy Is Free in Network Creation
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Title
Algorithms and Models for the Web Graph
Published by
Springer International Publishing, December 2013
DOI 10.1007/978-3-319-03536-9
ISBNs
978-3-31-903535-2, 978-3-31-903536-9
Editors

Bonato, Anthony, Mitzenmacher, Michael, Prałat, Paweł

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