Numerical algorithms for personalized search in self-organizing information networks / Sep Kamvar.

Format:

Book

Author/Creator:

Kamvar, Sep, 1977-

Language:

English

Subjects (All):

Database searching--Mathematics.

Database searching.

Information networks--Mathematics.

Information networks.

Content analysis (Communication)--Mathematics.

Content analysis (Communication).

Self-organizing systems--Data processing.

Self-organizing systems.

Algorithms.

Internet searching--Mathematics.

Internet searching.

Physical Description:

1 online resource (295 p.)

Edition:

Course Book

Place of Publication:

Princeton, N.J. : Princeton University Press, 2010.

Language Note:

English

Summary:

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 underlying personalized search and reputation management, and delves into realistic scenarios regarding Web-scale data. Sep Kamvar focuses on eigenvector-based techniques in Web search, introducing a personalized variant of Google's PageRank algorithm, and he outlines algorithms--such as the now-famous quadratic extrapolation technique--that speed up computation, making personalized PageRank feasible. Kamvar suggests that Power Method-related techniques ultimately should be the basis for improving the PageRank algorithm, and he presents algorithms that exploit the convergence behavior of individual components of the PageRank vector. Kamvar then extends the ideas of reputation management and personalized search to distributed networks like peer-to-peer and social networks. He highlights locality and computational considerations related to the structure of the network, and considers such unique issues as malicious peers. He describes the EigenTrust algorithm and applies various PageRank concepts to P2P settings. Discussion chapters summarizing results conclude the book's two main sections. Clear and thorough, this book provides an authoritative look at central innovations in search for all of those interested in the subject.

Contents:

Frontmatter

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. Eigen Trust

Chapter Ten. Adaptive P2P Topologies

Chapter Eleven. Conclusion

Bibliography

Notes:

Description based upon print version of record.

Includes bibliographical references.

ISBN:

9786612665844

9781282665842

1282665847

9781400837069

1400837065

OCLC:

650641334