Algorithms and Models for the Web-Graph
5th International Workshop, WAW 2007, San Diego, CA, USA, December 11-12, 2007, Proceedings
Published on 16. November 2007
Book
Paperback/Softback
X, 217 pages
978-3-540-77003-9 (ISBN)
Description
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.
More details
Series
Edition
2007 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
X, 217 p.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
361 gr
ISBN-13
978-3-540-77003-9 (9783540770039)
DOI
10.1007/978-3-540-77004-6
Schweitzer Classification
Content
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.