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Algorithms and Models for the Web Graph

18th International Workshop, WAW 2023, Toronto, ON, Canada, May 23–26, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Megan Dewar

    1. Tutte Institute for Mathematics and Computing, Ottawa, Canada

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  2. Paweł Prałat

    1. Toronto Metropolitan University, Toronto, Canada

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  3. Przemysław Szufel

    1. SGH Warsaw School of Economics, Warsaw, Poland

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  4. François Théberge

    1. Tutte Institute for Mathematics and Computing, Ottawa, Canada

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  5. Małgorzata Wrzosek

    1. SGH Warsaw School of Economics, Warsaw, Poland

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13894)

Included in the following conference series:

Conference proceedings info: WAW 2023.

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About this book

This book constitutes the proceedings of the 18th International Workshop on Algorithms and Models for the Web Graph, WAW 2023, held in Toronto, Canada, in May 23–26, 2023.The 12 Papers presented in this volume were carefully reviewed and selected from 21 submissions. The aim of the workshop was understanding of graphs that arise from the Web and various user activities on the Web, and stimulate the development of high-performance algorithms and applications that exploit these graphs.




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Table of contents (12 papers)

  1. Front Matter

    Pages i-x
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  2. Correcting for Granularity Bias in Modularity-Based Community Detection Methods

    • Martijn Gösgens, Remco van der Hofstad, Nelly Litvak
    Pages 1-18

  3. The Emergence of a Giant Component in One-Dimensional Inhomogeneous Networks with Long-Range Effects

    • Peter Gracar, Lukas Lüchtrath, Christian Mönch
    Pages 19-35

  4. Unsupervised Framework for Evaluating Structural Node Embeddings of Graphs

    • Ashkan Dehghan, Kinga Siuta, Agata Skorupka, Andrei Betlen, David Miller, Bogumił Kamiński et al.
    Pages 36-51

  5. Modularity Based Community Detection in Hypergraphs

    • Bogumił Kamiński, Paweł Misiorek, Paweł Prałat, François Théberge
    Pages 52-67

  6. Establishing Herd Immunity is Hard Even in Simple Geometric Networks

    • Michal Dvořák, Dušan Knop, Šimon Schierreich
    Pages 68-82

  7. Multilayer Hypergraph Clustering Using the Aggregate Similarity Matrix

    • Kalle Alaluusua, Konstantin Avrachenkov, B. R. Vinay Kumar, Lasse Leskelä
    Pages 83-98

  8. The Myth of the Robust-Yet-Fragile Nature of Scale-Free Networks: An Empirical Analysis

    • Rouzbeh Hasheminezhad, August Bøgh Rønberg, Ulrik Brandes
    Pages 99-111

  9. A Random Graph Model for Clustering Graphs

    • Fan Chung, Nicholas Sieger
    Pages 112-126

  10. Topological Analysis of Temporal Hypergraphs

    • Audun Myers, Cliff Joslyn, Bill Kay, Emilie Purvine, Gregory Roek, Madelyn Shapiro
    Pages 127-146

  11. PageRank Nibble on the Sparse Directed Stochastic Block Model

    • Sayan Banerjee, Prabhanka Deka, Mariana Olvera-Cravioto
    Pages 147-163

  12. A Simple Model of Influence

    • Colin Cooper, Nan Kang, Tomasz Radzik
    Pages 164-178

  13. The Iterated Local Transitivity Model for Tournaments

    • Anthony Bonato, Ketan Chaudhary
    Pages 179-192

  14. Back Matter

    Pages 193-193
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Other volumes

  1. Algorithms and Models for the Web Graph

Editors and Affiliations

  • Tutte Institute for Mathematics and Computing, Ottawa, Canada

    Megan Dewar, François Théberge

  • Toronto Metropolitan University, Toronto, Canada

    Paweł Prałat

  • SGH Warsaw School of Economics, Warsaw, Poland

    Przemysław Szufel, Małgorzata Wrzosek

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