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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 Finding Induced Subgraphs in Scale-Free Inhomogeneous Random Graphs
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    Chapter 2 The Asymptotic Normality of the Global Clustering Coefficient in Sparse Random Intersection Graphs
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    Chapter 3 Clustering Properties of Spatial Preferential Attachment Model
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    Chapter 4 Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities
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    Chapter 5 Joint Alignment from Pairwise Differences with a Noisy Oracle
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    Chapter 6 Analysis of Relaxation Time in Random Walk with Jumps
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    Chapter 7 QAP Analysis of Company Co-mention Network
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    Chapter 8 Towards a Systematic Evaluation of Generative Network Models
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    Chapter 9 Dynamic Competition Networks: Detecting Alliances and Leaders
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    Chapter 10 An Experimental Study of the k -MXT Algorithm with Applications to Clustering Geo-Tagged Data
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    Chapter 11 A Statistical Performance Analysis of Graph Clustering Algorithms
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Chapter title
An Experimental Study of the k -MXT Algorithm with Applications to Clustering Geo-Tagged Data
Chapter number 10
Book title
Algorithms and Models for the Web Graph
Published by
Springer, Cham, May 2018
DOI 10.1007/978-3-319-92871-5_10
Book ISBNs
978-3-31-992870-8, 978-3-31-992871-5
Authors

Colin Cooper, Ngoc Vu, Cooper, Colin, Vu, Ngoc

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