Algorithms and Models for the Web Graph - Info and Reading Options

The Open Library:

This book constitutes the refereed proceedings of the 11th International Workshop on Algorithms and Models for the Web Graph, WAW 2014, held in Beijing, China, in December 2014. The 12 papers presented were carefully reviewed and selected for inclusion in this volume. 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. The workshop gathered the researchers who are working on graph-theoretic and algorithmic aspects of related complex networks, including social networks, citation networks, biological networks, molecular networks, and other networks arising from the Internet.

Open Data:

Intro -- Preface -- Organization -- Contents -- Clustering and the Hyperbolic Geometry of Complex Networks -- 1 Introduction -- 1.1 Random Geometric Graphs on the Hyperbolic Plane -- 1.2 Notation -- 2 Some Geometric Aspects of the Two Models -- 3 The Clustering Coefficient -- 4 Conclusions -- References -- Burning a Graph as a Model of Social Contagion -- 1 Introduction -- 2 Properties of the Burning Number -- 2.1 Characterizations of Burning Number via Trees -- 2.2 Bounds -- 3 Burning in the ILT Model -- 4 Cartesian Grids -- 5 Conclusions and Future Work -- References -- Personalized PageRank with Node-Dependent Restart -- 1 Introduction and Definitions -- 2 Occupation-Time Personalized PageRank -- 3 Location-of-Restart Personalized PageRank -- 4 Interesting Particular Cases -- 4.1 Constant Probability of Restart -- 4.2 Restart Probabilities Proportional to Powers of Degrees -- 4.3 Random Walk with Jumps -- 5 Discussion -- References -- Efficient Computation of the Weighted Clustering Coefficient -- 1 Introduction -- 1.1 Related Works -- 2 Preliminaries -- 2.1 Generalizations of Clustering Coefficient in Weighted Networks -- 3 Computing the Weighted Clustering Coefficient in Probabilistic Networks -- 4 Efficient Estimators for the Weighted Clustering Coefficient -- 5 Experiments -- References -- Global Clustering Coefficient in Scale-Free Networks -- 1 Introduction -- 2 Clustering Coefficients -- 3 Scale-Free Graphs -- 4 Existence of a Graph with Given Degree Distribution -- 4.1 Result -- 4.2 Auxiliary Results -- 4.3 Proof of Theorem 1 -- 5 Global Clustering Coefficient -- 5.1 Result -- 5.2 Proof of Theorem 4 -- 6 Experiments -- 7 Conclusion -- References -- Efficient Primal-Dual Graph Algorithms for MapReduce -- 1 Introduction -- 1.1 Problem Formulations and Results -- 1.2 Technique: Width Modulation -- 1.3 Related Work

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