Algorithms and Models for the Web Graph

17th International Workshop, WAW 2020, Warsaw, Poland, September 21-22, 2020, Proceedings
Springer (Verlag)
  • 1. Auflage
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  • erschienen am 14. Mai 2020
  • Buch
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  • Softcover
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  • 184 Seiten
978-3-030-48477-4 (ISBN)
This book constitutes the proceedings of the 17th International Workshop on Algorithms and Models for the Web Graph, WAW 2020, held in Warsaw, Poland, in September 2020. The 12 full papers presented in this volume were carefully reviewed and selected from 19 submissions. The aim of the workshop was to further the 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.
Due to the corona pandemic the conference was postponed from June 2020 to September 2020.
1st ed. 2020
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • Für Beruf und Forschung
  • 11 s/w Abbildungen, 29 farbige Abbildungen
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  • 29 Illustrations, color; 11 Illustrations, black and white; X, 173 p. 40 illus., 29 illus. in color.
  • Höhe: 235 mm
  • |
  • Breite: 155 mm
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  • Dicke: 10 mm
  • 289 gr
978-3-030-48477-4 (9783030484774)
weitere Ausgaben werden ermittelt

Hypergraph Analytics of Domain Name System Relationships.- Global Graph Curvature.- Information Diffusion in Complex Networks: a Model Based on Hypergraphs and its Analysis.- A Scalable Unsupervised Framework for Comparing Graph Embeddings.- Assortativity and Bidegree Distributions on Bernoulli Random Graph Superpositions.- Clustering Coefficient of a Preferred Attachment Affiliation Network.- Transience Versus Recurrence for Scale-Free Spatial Networks.- The Iterated Local Directed Transitivity Model for Social Networks.- A note on the conductance of the binomial random intersection graph.- Iterated Global Models for Complex Networks.- A Robust Method for Statistical Testing of Empirical Power-Law Distributions.- Community Structures in Information Networks for a Discrete Agent Population.

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