You are previewing Google's PageRank and Beyond.

Google's PageRank and Beyond

Cover of Google's PageRank and Beyond by Amy N. Langville... Published by Princeton University Press
  1. Cover
  2. Half title
  3. Title
  4. Contents
  5. Preface
  6. Chapter 1. Introduction to Web Search Engines
    1. 1.1 A Short History of Information Retrieval
    2. 1.2 An Overview of Traditional Information Retrieval
    3. 1.3 Web Information Retrieval
  7. Chapter 2. Crawling, Indexing, and Query Processing
    1. 2.1 Crawling
    2. 2.2 The Content Index
    3. 2.3 Query Processing
  8. Chapter 3. Ranking Webpages by Popularity
    1. 3.1 The Scene in 1998
    2. 3.2 Two Theses
    3. 3.3 Query-Independence
  9. Chapter 4. The Mathematics of Google’s PageRank
    1. 4.1 The Original Summation Formula for PageRank
    2. 4.2 Matrix Representation of the Summation Equations
    3. 4.3 Problems with the Iterative Process
    4. 4.4 A Little Markov Chain Theory
    5. 4.5 Early Adjustments to the Basic Model
    6. 4.6 Computation of the PageRank Vector
    7. 4.7 Theorem and Proof for Spectrum of the Google Matrix
  10. Chapter 5. Parameters in the PageRank Model
    1. 5.1 The α Factor
    2. 5.2 The Hyperlink Matrix H
    3. 5.3 The Teleportation Matrix E
  11. Chapter 6. The Sensitivity of PageRank
    1. 6.1 Sensitivity with respect to α
    2. 6.2 Sensitivity with respect to H
    3. 6.3 Sensitivity with respect to v
    4. 6.4 Other Analyses of Sensitivity
    5. 6.5 Sensitivity Theorems and Proofs
  12. Chapter 7. The PageRank Problem as a Linear System
    1. 7.1 Properties of (I − αS)
    2. 7.2 Properties of (I − αH)
    3. 7.3 Proof of the PageRank Sparse Linear System
  13. Chapter 8. Issues in Large-Scale Implementation of PageRank
    1. 8.1 Storage Issues
    2. 8.2 Convergence Criterion
    3. 8.3 Accuracy
    4. 8.4 Dangling Nodes
    5. 8.5 Back Button Modeling
  14. Chapter 9. Accelerating the Computation of PageRank
    1. 9.1 An Adaptive Power Method
    2. 9.2 Extrapolation
    3. 9.3 Aggregation
    4. 9.4 Other Numerical Methods
  15. Chapter 10. Updating the PageRank Vector
    1. 10.1 The Two Updating Problems and their History
    2. 10.2 Restarting the Power Method
    3. 10.3 Approximate Updating Using Approximate Aggregation
    4. 10.4 Exact Aggregation
    5. 10.5 Exact vs. Approximate Aggregation
    6. 10.6 Updating with Iterative Aggregation
    7. 10.7 Determining the Partition
    8. 10.8 Conclusions
  16. Chapter 11. The HITS Method for Ranking Webpages
    1. 11.1 The HITS Algorithm
    2. 11.2 HITS Implementation
    3. 11.3 HITS Convergence
    4. 11.4 HITS Example
    5. 11.5 Strengths and Weaknesses of HITS
    6. 11.6 HITS’s Relationship to Bibliometrics
    7. 11.7 Query-Independent HITS
    8. 11.8 Accelerating HITS
    9. 11.9 HITS Sensitivity
  17. Chapter 12. Other Link Methods for Ranking Webpages
    1. 12.1 SALSA
    2. 12.2 Hybrid Ranking Methods
    3. 12.3 Rankings based on Traffic Flow
  18. Chapter 13. The Future of Web Information Retrieval
    1. 13.1 Spam
    2. 13.2 Personalization
    3. 13.3 Clustering
    4. 13.4 Intelligent Agents
    5. 13.5 Trends and Time-Sensitive Search
    6. 13.6 Privacy and Censorship
    7. 13.7 Library Classification Schemes
    8. 13.8 Data Fusion
  19. Chapter 14. Resources for Web Information Retrieval
    1. 14.1 Resources for Getting Started
    2. 14.2 Resources for Serious Study
  20. Chapter 15. The Mathematics Guide
    1. 15.1 Linear Algebra
    2. 15.2 Perron–Frobenius Theory
    3. 15.3 Markov Chains
    4. 15.4 Perron Complementation
    5. 15.5 Stochastic Complementation
    6. 15.6 Censoring
    7. 15.7 Aggregation
    8. 15.8 Disaggregation
  21. Chapter 16. Glossary
  22. Bibliography
  23. Index
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Bibliography

[1] Caslon Analytics net metrics and statistics guide. http://www.caslon.com.au/metricsguide.htm.

[2] Clever—IBM Corporation Almaden Research Center. http://www.almaden.ibm.com/cs/k53/clever.html.

[3] Text REtrieval Conference. http://trec.nist.gov/.

[4] World Wide Web Conference. http://www2004.org.

[5] How much information, 2003. http://www.sims.berkeley.edu/howmuch-info-2003.

[6] Medlars test collection, December 2003. Available at http://www.cs.utk.edu/~lsi/.

[7] Why does my page’s rank keep changing? Google PageRank information. http://www.google.com/webmasters/4.html, 2003.

[8] Eytan Adar, Li Zhang, Lada A. Adamic, and Rajan ...

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