Numerical algorithms for personalized search in self-organizing information networks

This book lays out the theoretical groundwork for personalized search and reputation management, both on the Web and in peer-to-peer and social networks. Representing much of the foundational research in this field, the book develops scalable algorithms that exploit the graphlike properties underlyi...

Full description

Saved in:
Bibliographic Details
Main Author Kamvar, Sep
Format eBook Book
LanguageEnglish
Published Princeton, N.J Princeton University Press 2010
Edition1
Subjects
Algorithms
COMPUTERS
COMPUTERS / Computer Science
Content analysis
Content analysis (Communication)
Content analysis (Communication) > Mathematics
Data processing
Database searching
Database searching > Mathematics
Information networks
Information networks > Mathematics
Internet searching
Internet searching > Mathematics
Mathematics
Ratings and rankings
Self-organizing systems
Self-organizing systems > Data processing
Technology
Web sites
Online AccessGet full text

Cover

Table of Contents:
  • Numerical algorithms for personalized search in self-organizing information networks -- Contents -- Tables -- Figures -- Acknowledgments -- Chapter One: Introduction -- Part I: World Wide Web -- Chapter Two: PageRank -- Chapter Three: The Second Eigenvalue of the Google Matrix -- Chapter Four: The Condition Number of the PageRank Problem -- Chapter Five: Extrapolation Algorithms -- Chapter Six: Adaptive PageRank -- Chapter Seven: BlockRank -- Part II: P2P Networks -- Chapter Eight: Query-Cycle Simulator -- Chapter Nine: EigenTrust -- Chapter Ten: Adaptive P2P Topologies -- Chapter Eleven: Conclusion -- Bibliography
  • Front Matter Table of Contents Tables Figures Acknowledgments Chapter One: Introduction Chapter Two: PageRank Chapter Three: The Second Eigenvalue of the Google Matrix Chapter Four: The Condition Number of the PageRank Problem Chapter Five: Extrapolation Algorithms Chapter Six: Adaptive PageRank Chapter Seven: BlockRank Chapter Eight: Query-Cycle Simulator Chapter Nine: EigenTrust Chapter Ten: Adaptive P2P Topologies Chapter Eleven: Conclusion Bibliography
  • 10.4.1 Malicious Peers Move to Fringe -- 10.4.2 Freeriders Move to Fringe -- 10.4.3 Active Peers Are Rewarded -- 10.4.4 Efficient Topology -- 10.5 Threat Scenarios -- 10.5.1 Threat Model A -- 10.5.2 Threat Model B -- 10.5.3 Threat Model C -- 10.6 Related Work -- 10.7 Discussion -- Chapter 11 Conclusion -- Bibliography
  • Intro -- Numerical Algorithms for Personalized Search in Self-organizing Information Networks -- Contents -- Tables -- Figures -- Acknowledgments -- Chapter 1 Introduction -- 1.1 World Wide Web -- 1.2 P2P Networks -- 1.3 Contributions -- PART I WORLD WIDE WEB -- Chapter 2 PageRank -- 2.1 PageRank Basics -- 2.2 Notation and Mathematical Preliminaries -- 2.3 Power Method -- 2.3.1 Formulation -- 2.3.2 Operation Count -- 2.3.3 Convergence -- 2.4 Experimental Setup -- 2.5 Related Work -- 2.5.1 Fast Eigenvector Computation -- 2.5.2 PageRank -- Chapter 3 The Second Eigenvalue of the Google Matrix -- 3.1 Introduction -- 3.2 Theorems -- 3.3 Proof of Theorem 1 -- 3.4 Proof of Theorem 2 -- 3.5 Implications -- 3.6 Theorems Used -- Chapter 4 The Condition Number of the PageRank Problem -- 4.1 Theorem 6 -- 4.2 Proof of Theorem 6 -- 4.3 Implications -- Chapter 5 Extrapolation Algorithms -- 5.1 Introduction -- 5.2 Aitken Extrapolation -- 5.2.1 Formulation -- 5.2.2 Operation Count -- 5.2.3 Experimental Results -- 5.2.4 Discussion -- 5.3 Quadratic Extrapolation -- 5.3.1 Formulation -- 5.3.2 Operation Count -- 5.3.3 Experimental Results -- 5.3.4 Discussion -- 5.4 Power Extrapolation -- 5.4.1 Simple Power Extrapolation -- 5.4.2 A2 Extrapolation -- 5.4.3 Ad Extrapolation -- 5.5 Measures of Convergence -- Chapter 6 Adaptive PageRank -- 6.1 Introduction -- 6.2 Distribution of Convergence Rates -- 6.3 Adaptive PageRank Algorithm -- 6.3.1 Algorithm Intuition -- 6.3.2 Filter-based Adaptive PageRank -- 6.4 Experimental Results -- 6.5 Extensions -- 6.5.1 Further Reducing Redundant Computation -- 6.5.2 Using the Matrix Ordering from the Previous Computation -- 6.6 Discussion -- Chapter 7 BlockRank -- 7.1 Block Structure of the Web -- 7.1.1 Block Sizes -- 7.1.2 The GeoCities Effect -- 7.2 BlockRank Algorithm -- 7.2.1 Overview of BlockRank Algorithm
  • 7.2.2 Computing Local PageRanks -- 7.2.3 Estimating the Relative Importance of Each Block -- 7.2.4 Approximating Global PageRank Using Local PageRank and BlockRank -- 7.2.5 Using This Estimate as a Start Vector -- 7.3 Advantages of BlockRank -- 7.4 Experimental Results -- 7.5 Discussion -- 7.6 Personalized PageRank -- 7.6.1 Inducing Random Jump Probabilities over Pages -- 7.6.2 Using "Better" Local PageRanks -- 7.6.3 Experiments -- 7.6.4 Topic-Sensitive PageRank -- 7.6.5 Pure BlockRank -- PART II P2P NETWORKS -- Chapter 8 Query-Cycle Simulator -- 8.1 Challenges in Empirical Evaluation of P2P Algorithms -- 8.2 The Query-Cycle Model -- 8.3 Basic Properties -- 8.3.1 Network Topology -- 8.3.2 Joining the Network -- 8.3.3 Query Propagation -- 8.4 Peer-Level Properties -- 8.5 Content Distribution Model -- 8.5.1 Data Volume -- 8.5.2 Content Type -- 8.6 Peer Behavior Model -- 8.6.1 Uptime and Session Duration -- 8.6.2 Query Activity -- 8.6.3 Queries -- 8.6.4 Query Responses -- 8.6.5 Downloads -- 8.7 Network Parameters -- 8.7.1 Topology -- 8.7.2 Bandwidth -- 8.8 Discussion -- Chapter 9 EigenTrust -- 9.1 Design Considerations -- 9.2 Reputation Systems -- 9.3 EigenTrust -- 9.3.1 Normalizing Local Trust Values -- 9.3.2 Aggregating Local Trust Values -- 9.3.3 Probabilistic Interpretation -- 9.3.4 Basic EigenTrust -- 9.3.5 Practical Issues -- 9.3.6 Distributed EigenTrust -- 9.3.7 Algorithm Complexity -- 9.4 Secure EigenTrust -- 9.4.1 Algorithm Description -- 9.4.2 Discussion -- 9.5 Using Global Trust Values -- 9.6 Experiments -- 9.6.1 Load Distribution in a Trust-based Network -- 9.6.2 Threat Models -- 9.7 Related Work -- 9.8 Discussion -- Chapter 10 Adaptive P2P Topologies -- 10.1 Introduction -- 10.2 Interaction Topologies -- 10.3 Adaptive P2P Topologies -- 10.3.1 Local Trust Scores -- 10.3.2 Protocol -- 10.3.3 Practical Issues -- 10.4 Empirical Results
  • Acknowledgments --
  • Chapter Two. PageRank --
  • Contents --
  • Chapter Seven. BlockRank --
  • Tables --
  • Chapter One. Introduction --
  • Chapter Six. Adaptive PageRank --
  • Chapter Five. Extrapolation Algorithms --
  • PART II. P2P Networks --
  • Chapter Eight. Query-Cycle Simulator --
  • Chapter Eleven. Conclusion --
  • Chapter Three. The Second Eigenvalue of the Google Matrix --
  • Figures --
  • Chapter Nine. Eigen Trust --
  • Chapter Ten. Adaptive P2P Topologies --
  • Chapter Four. The Condition Number of the PageRank Problem --
  • Frontmatter --
  • PART I. World Wide Web --
  • Bibliography