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9th International Workshop, WAW 2012, Halifax, NS, Canada, June 22-23, 2012. Proceedings

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The cover of “Algorithms and Models for the Web Graph” - Open Library.

"Algorithms and Models for the Web Graph" was published by Springer Berlin Heidelberg in 2012 - Berlin, Heidelberg, it has 1 pages and the language of the book is English.


“Algorithms and Models for the Web Graph” Metadata:

  • Title: ➤  Algorithms and Models for the Web Graph
  • Author:
  • Language: English
  • Number of Pages: 1
  • Publisher: Springer Berlin Heidelberg
  • Publish Date:
  • Publish Location: Berlin, Heidelberg

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"Algorithms and Models for the Web Graph" Description:

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Title -- Preface -- Table of Contents -- Hypergraph Coloring Games and Voter Models -- Introduction -- The Voting Game on a Hypergraph as a Random Walk on the Associated State Graph -- Memoryless Interactions and Semigroup Spectral Graph Theory -- The Cut-Off Time for Voter Interaction Games -- Estimating the Expected Value of a Given Event -- The Interaction Model with Partially Memoryless Interactions -- The General Interaction Model -- References -- Semigroup Details for Proving Theorem 3 -- Proof of Theorem 5 -- Proof of Theorem 7 -- On a DAG Partitioning Problem -- Introduction -- The Hardness Result -- Linear-Time Algorithm for Bounded-Pathwidth Graphs -- Concluding Remarks -- References -- Some Typical Properties of the Spatial Preferred Attachment Model -- Introduction -- The SPA Model -- Directed Diameter -- Upper Bound -- Lower Bound -- Small Separators -- Emergence of Giant Component -- References -- A Sublinear Time Algorithm for PageRank Computations -- Introduction -- Identifying Nodes with Significant PageRanks: Our Results -- Matrix Sampling and Personalized PageRank Approximation -- Additional Related Work -- Organization -- Preliminaries -- Multi-scale Matrix Sampling and Approximation of PageRank -- Lower Bound Construction for PageRank Approximations -- Local Robust Computation of Personalized PageRank -- References -- Quick Detection of Nodes with Large Degrees -- Introduction -- Random Walk with Uniform Jumps -- Estimating the Largest Degrees in the Configuration Network Model -- Stopping Criteria -- Relaxation of Top k Lists -- Conclusions and Future Research -- References -- Ranking and Sparsifying a Connection Graph -- Introduction -- Preliminaries -- The Connection Laplacian -- The Consistency of a Connection Graph -- Random Walks on a Connection Graph -- PageRank Vectors in a Connection Graph

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