Algorithms and Models for the Web Graph

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Details

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.

Inhalt

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.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783030484774
    • Editor Bogumi Kami ski, Przemys aw Szufel, Pawe Pra at
    • Sprache Englisch
    • Auflage 1st edition 2020
    • Größe H235mm x B155mm x T11mm
    • Jahr 2020
    • EAN 9783030484774
    • Format Kartonierter Einband
    • ISBN 3030484777
    • Veröffentlichung 14.05.2020
    • Titel Algorithms and Models for the Web Graph
    • Untertitel 17th International Workshop, WAW 2020, Warsaw, Poland, September 21-22, 2020, Proceedings
    • Gewicht 289g
    • Herausgeber Springer International Publishing
    • Anzahl Seiten 184
    • Lesemotiv Verstehen
    • Genre Informatik

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