Algorithms and Models for the Web-Graph

5th International Workshop, WAW 2007, San Diego, CA, USA, December 11-12, 2007, Proceedings

AvAnthony Bonato,Fan R.K. Chung

Häftad, Engelska, 2007

Del i serien Lecture Notes in Computer Science

574 kr

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Beskrivning

This book constitutes the refereed proceedings of the 5th International Workshop on Algorithms and Models for the Web-Graph, WAW 2007, held in San Diego, CA, USA, in December 2007 - colocated with WINE 2007, the Third International Workshop on Internet and Network Economics. The 13 revised full papers and five revised short papers presented were carefully reviewed and selected from a large pool of submissions for inclusion in the book. The papers address a wide variety of topics.

Produktinformation

Utgivningsdatum:2007-11-16
Mått:155 x 235 x undefined mm
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:217
Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN:9783540770039

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Innehållsförteckning

Bias Reduction in Traceroute Sampling – Towards a More Accurate Map of the Internet.- Distribution of PageRank Mass Among Principle Components of the Web.- Finding a Dense-Core in Jellyfish Graphs.- A Geometric Preferential Attachment Model of Networks II.- Clustering Social Networks.- Manipulation-Resistant Reputations Using Hitting Time.- Using Polynomial Chaos to Compute the Influence of Multiple Random Surfers in the PageRank Model.- A Spatial Web Graph Model with Local Influence Regions.- Determining Factors Behind the PageRank Log-Log Plot.- Approximating Betweenness Centrality.- Random Dot Product Graph Models for Social Networks.- Local Computation of PageRank Contributions.- Local Partitioning for Directed Graphs Using PageRank.- Stochastic Kronecker Graphs.- Deterministic Decentralized Search in Random Graphs.- Using Bloom Filters to Speed Up HITS-Like Ranking Algorithms.- Parallelizing the Computation of PageRank.- Giant Component and Connectivity in Geographical Threshold Graphs.