Numerical algorithms for personalized search in self-organizing information networks:
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Bibliographische Detailangaben
1. Verfasser: Kamvar, Sep (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Princeton Princeton University Press ©2010
Schlagworte:
Online-Zugang:FAW01
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Beschreibung:Includes bibliographical references (pages 135-139)
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; Chapter 3 The Second Eigenvalue of the Google Matrix; Chapter 4 The Condition Number of the PageRank Problem; Chapter 5 Extrapolation Algorithms; Chapter 6 Adaptive PageRank; Chapter 7 BlockRank; PART II P2P NETWORKS; Chapter 8 Query-Cycle Simulator; Chapter 9 EigenTrust; Chapter 10 Adaptive P2P Topologies; Chapter 11 Conclusion; Bibliography
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 quad
Beschreibung:1 Online-Ressource (xiv, 139 pages)
ISBN:1282665847
1400837065
9781282665842
9781400837069

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