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Understanding Search Engines

Understanding Search Engines
Mathematical Modeling and Text Retrieval

2nd Edition

£31.99

Part of Software, Environments and Tools

  • Date Published: May 2005
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • format: Paperback
  • isbn: 9780898715811

£ 31.99
Paperback

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  • The second edition of Understanding Search Engines: Mathematical Modeling and Text Retrieval follows the basic premise of the first edition by discussing many of the key design issues for building search engines and emphasizing the important role that applied mathematics can play in improving information retrieval. The authors discuss important data structures, algorithms, and software as well as user-centered issues such as interfaces, manual indexing, and document preparation. Significant changes bring the text up to date on current information retrieval methods: for example the addition of a new chapter on link-structure algorithms used in search engines such as Google. The chapter on user interface has been rewritten to specifically focus on search engine usability. In addition the authors have added new recommendations for further reading and expanded the bibliography, and have updated and streamlined the index to make it more reader friendly.

    • Serves as an excellent companion text for courses in information retrieval, applied linear algebra, and scientific computing
    • The authors' informal, conversational tone allows readers with non-mathematical backgrounds to appreciate the less technical chapters of the text
    • This second edition includes significant changes that bring the text up-to-date on current information retrieval methods
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    Reviews & endorsements

    'There is no other information retrieval/search book where the heart is the mathematical foundations. This book is greatly needed to further establish information retrieval as a serious academic, as well as practical and industrial, area.' Jaime Carbonell, Carnegie Mellon University

    'Berry and Browne describe most of what you need to know to design your own search engine. Their strength is the description of the solid mathematical underpinnings at a level that is understandable to competent engineering undergraduates, perhaps with a bit of instructor guidance. They discuss the algorithms used by most commercial search engines, so you may find your use of Google and its kind becomes more effective, too.' George Corliss, Marquette University.

    'This book gives a valuable, generally non-technical, insight into how search engines work, how to improve the users' success in Information Retrieval (IR), and an in-depth analysis of a mathematical algorithm for improving a search engine's performance. …Written in an informal style, the book is easy to read and is a good introduction on how search engines operate…' Christopher Dean, Mathematics Today

    'Anyone interested in building their own search engine, or looking for a compact and readable introduction to the field of modern information retrieval will find this book to be an excellent first introduction.' Tony Donaldson, MAA Reviews

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    Product details

    • Edition: 2nd Edition
    • Date Published: May 2005
    • format: Paperback
    • isbn: 9780898715811
    • length: 184 pages
    • dimensions: 228 x 152 x 9 mm
    • weight: 0.193kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • Table of Contents

    Preface to the second edition
    Preface to the first edition
    1. Introduction
    2. Document file preparation
    3. Vector space models
    4. Matrix decompositions
    5. Query management
    6. Ranking and relevance feedback
    7. Searching by link structure
    8. User interface considerations
    9. Further reading
    Bibliography
    Index.

  • Authors

    Michael W. Berry, University of Tennessee, Knoxville

    Murray Browne, University of Tennessee, Knoxville

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