Algorithms and Models for the Web Graph
18th International Workshop, WAW 2023, Toronto, ON, Canada, May 23-26, 2023, Proceedings
Published on 15. May 2023
X, 193 pages
978-3-031-32296-9 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
X, 193 p. 54 illus., 43 illus. in color.
File size
10,04 MB
ISBN-13
978-3-031-32296-9 (9783031322969)
DOI
10.1007/978-3-031-32296-9
Schweitzer Classification
Other editions
Additional editions
Megan Dewar | Pawel Pralat | Przemyslaw Szufel
Algorithms and Models for the Web Graph
18th International Workshop, WAW 2023, Toronto, ON, Canada, May 23-26, 2023, Proceedings
Book
04/2023
Springer
€58.84
Shipment within 15-20 days
Content
Correcting for Granularity Bias in Modularity-Based Community Detection Methods.- The emergence of a giant component in one-dimensional inhomogeneous networks with long-range effects.- Unsupervised Framework for Evaluating Structural Node Embeddings of Graphs.- Modularity Based Community Detection in Hypergraphs.- Establishing Herd Immunity is Hard Even in Simple Geometric Networks.- Multilayer hypergraph clustering using the aggregate similarity matrix.- The Myth of the Robust-Yet-Fragile Nature of Scale-Free Networks: An Empirical Analysis.- A Random Graph Model for Clustering Graphs.- Topological Analysis of Temporal Hypergraphs.- PageRank Nibble on the sparse directed stochastic block model.- A simple model of influence.- The Iterated Local Transitivity Model for Tournaments.
