Your Waterstones card is changing, introducing...
TELL ME MORE
Numerical Algorithms for Personalized Search in Self-organizing Information Networks (Hardback)
  • Numerical Algorithms for Personalized Search in Self-organizing Information Networks (Hardback)
zoom

Numerical Algorithms for Personalized Search in Self-organizing Information Networks (Hardback)

(author)
£47.00
Hardback 160 Pages / Published: 08/10/2010
  • We can order this

Usually despatched within 1 week

  • This item has been added to your basket
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.

Publisher: Princeton University Press
ISBN: 9780691145037
Number of pages: 160
Weight: 397 g
Dimensions: 235 x 152 x 11 mm


MEDIA REVIEWS
"The writing style is extremely clear, and the book is accessible to readers both within and outside of the field."--Chen Greif, University of British Columbia
"The clarity of presentation makes this book accessible to a broad audience. The scholarship is thorough and sound, and the experimental results are presented in a precise and detailed fashion."--Taher Haveliwala, QForge Labs
"Kamvar helped establish a foundation for P2P search and this book provides an authoritative record and source for his excellent work in this area."--Andrew Tomkins, Google

You may also be interested in...

Assembly Language Step-by-Step
Added to basket
Portfolio, programme and project offices
Added to basket
Machine Learning
Added to basket
How to Pass Higher Computing Science
Added to basket
£11.99   £8.99
Paperback
Machine Learning
Added to basket
£42.50
Paperback
Computing with Quantum Cats
Added to basket
The Elements of Statistical Learning
Added to basket
Blockchain
Added to basket
£19.99
Paperback
Data Science from Scratch
Added to basket
Introducing Artificial Intelligence
Added to basket
Artificial Intelligence: The Basics
Added to basket
Computer Science: An Overview, Global Edition
Added to basket

Reviews

Please sign in to write a review

Your review has been submitted successfully.