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Introduction to Information Retrieval

$71.99 (X)

  • Date Published: July 2008
  • availability: In stock
  • format: Hardback
  • isbn: 9780521865715

$ 71.99 (X)

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About the Authors
  • Class-tested and coherent, this groundbreaking new textbook teaches web-era information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.

    • Introduces all key concepts, requiring little prior knowledge
    • All concepts are illustrated with figures and examples
    • Supporting web site features lecture slides that follow the book, and a solutions manual for lecturers
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    Reviews & endorsements

    “This is the first book that gives you a complete picture of the complications that arise in building a modern web-scale search engine. You'll learn about ranking SVMs, XML, DNS, and LSI. You'll discover the seedy underworld of spam, cloaking, and doorway pages. You'll see how MapReduce and other approaches to parallelism allow us to go beyond megabytes and to efficiently manage petabytes."
    Peter Norvig, Director of Research, Google Inc.

    "Introduction to Information Retrieval is a comprehensive, up-to-date, and well-written introduction to an increasingly important and rapidly growing area of computer science. Finally, there is a high-quality textbook for an area that was desperately in need of one."
    Raymond J. Mooney, Professor of Computer Sciences, University of Texas at Austin

    “Through compelling exposition and choice of topics, the authors vividly convey both the fundamental ideas and the rapidly expanding reach of information retrieval as a field.”
    Jon Kleinberg, Professor of Computer Science, Cornell University

    "Highly recommended."
    H.Levkowitz, Choice Magazine

    "Introduction to Information Retrieval is a comprehensive, authoritative, and well-written overview of the main topics in IR. The book offers a good balance of theory and practice, and is an excellent self-contained introductory text for those new to IR."
    Olga Vechtomova, Computational Linguistics

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    Product details

    • Date Published: July 2008
    • format: Hardback
    • isbn: 9780521865715
    • length: 506 pages
    • dimensions: 260 x 185 x 31 mm
    • weight: 1.03kg
    • contains: 5 b/w illus. 47 tables 263 exercises
    • availability: In stock
  • Table of Contents

    1. Information retrieval using the Boolean model
    2. The dictionary and postings lists
    3. Tolerant retrieval
    4. Index construction
    5. Index compression
    6. Scoring and term weighting
    7. Vector space retrieval
    8. Evaluation in information retrieval
    9. Relevance feedback and query expansion
    10. XML retrieval
    11. Probabilistic information retrieval
    12. Language models for information retrieval
    13. Text classification and Naive Bayes
    14. Vector space classification
    15. Support vector machines and kernel functions
    16. Flat clustering
    17. Hierarchical clustering
    18. Dimensionality reduction and latent semantic indexing
    19. Web search basics
    20. Web crawling and indexes
    21. Link analysis.

  • Resources for

    Introduction to Information Retrieval

    Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze

    General Resources

    Instructor Resources

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    Here you will find free-of-charge online materials to accompany this book. The range of materials we provide across our academic and higher education titles are an integral part of the book package whether you are a student, instructor, researcher or professional.

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    These resources are provided free of charge by Cambridge University Press with permission of the author of the corresponding work, but are subject to copyright. You are permitted to view, print and download these resources for your own personal use only, provided any copyright lines on the resources are not removed or altered in any way. Any other use, including but not limited to distribution of the resources in modified form, or via electronic or other media, is strictly prohibited unless you have permission from the author of the corresponding work and provided you give appropriate acknowledgement of the source.

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  • Instructors have used or reviewed this title for the following courses

    • Advanced Topics in Information Security
    • Cloud Computing for Data Analysis
    • Computational Linguistics
    • Data Mining
    • Data Mining and Knowledge Discovery
    • From Languages to Information
    • Info & Text Retrieval
    • Information Organization and Retrieval
    • Information Retrieval & Data Mining
    • Information Retrieval Systems
    • Information Retrieval and Web Search
    • Information Storage and Retrieval
    • Internet and Web Systems
    • Mathematical Tools for the Information Sciences
    • Search Engine Technology
    • Senior Seminar in Computer Science
    • Software Engineering ll
    • Specials topics course on IR
    • Topics in Information Retrieval
    • Web Information Exploration
    • Web Search and Information Retrieval
    • Web Search and Text Mining
  • Authors

    Christopher D. Manning, Stanford University, California
    Christopher Manning is an Associate Professor of Computer Science and Linguistics at Stanford University. His research concentrates on probabilistic models of language and statistical natural language processing, information extraction, text understanding and text mining.

    Prabhakar Raghavan, Google, Inc.
    Dr Prabhakar Raghavan is Head of Yahoo! Research and a Consulting Professor of Computer Science at Stanford University.

    Hinrich Schütze, Universität Stuttgart
    Dr Hinrich Schütze resides as Chair of Theoretical Computational Linguistics at the Institute for Natural Language Processing, University of Stuttgart.

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