© 2004

Information Retrieval

Algorithms and Heuristics


Part of the The Kluwer International Series on Information Retrieval book series (INRE, volume 15)

Table of contents

  1. Front Matter
    Pages i-xix
  2. David A. Grossman, Ophir Frieder
    Pages 1-8
  3. David A. Grossman, Ophir Frieder
    Pages 9-92
  4. David A. Grossman, Ophir Frieder
    Pages 93-147
  5. David A. Grossman, Ophir Frieder
    Pages 149-179
  6. David A. Grossman, Ophir Frieder
    Pages 181-209
  7. David A. Grossman, Ophir Frieder
    Pages 211-255
  8. David A. Grossman, Ophir Frieder
    Pages 257-274
  9. David A. Grossman, Ophir Frieder
    Pages 275-290
  10. David A. Grossman, Ophir Frieder
    Pages 291-298
  11. Back Matter
    Pages 299-332

About this book


Interested in how an efficient search engine works? Want to know what algorithms are used to rank resulting documents in response to user requests? The authors answer these and other key information retrieval design and implementation questions.

This book is not yet another high level text. Instead, algorithms are thoroughly described, making this book ideally suited for both computer science students and practitioners who work on search-related applications. As stated in the foreword, this book provides a current, broad, and detailed overview of the field and is the only one that does so. Examples are used throughout to illustrate the algorithms.

The authors explain how a query is ranked against a document collection using either a single or a combination of retrieval strategies, and how an assortment of utilities are integrated into the query processing scheme to improve these rankings. Methods for building and compressing text indexes, querying and retrieving documents in multiple languages, and using parallel or distributed processing to expedite the search are likewise described.

This edition is a major expansion of the one published in 1998. Besides updating the entire book with current techniques, it includes new sections on language models, cross-language information retrieval, peer-to-peer processing, XML search, mediators, and duplicate document detection.


Analysis Extensible Markup Language (XML) Text XML algorithms computer computer science genetic algorithm heuristics knowledge neural network

Authors and affiliations

  1. 1.Illinois Institute of TechnologyChicagoUSA

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