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Introduction to Information Retrieval

$69.00

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

$69.00
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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: 496 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.

  • general resources

    instructor resources

    View all resources
    Group Section Name Type Size Sort Order filter vars
    General ResourcesSlidesChapter 8: Evaluations & results summarieszip15453KB0slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 5: Index compressionzip7432KB1slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 4: Index constructionzip8835KB2slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 14: Vector Classificationzip8591KB3slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 9: Relevance feedback and query expansionzip17023KB4slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 7: Scores in a complete search systemzip12815KB5slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 6: Scoring term weighting, the vector space modelzip10642KB6slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 13: Text classification and naive bayeszip9787KB7slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 21: Link Analysiszip7682KB8slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 16: Flat clusteringzip12919KB9slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 3: Dictionaries and tolerant retrievalzip10533KB10slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 1: Boolean retrievalzip3792KB11slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 20: Crawlingzip2002KB12slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 19: Web Search Basicszip13065KB13slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 2: The term vocabulary and posting listszip8301KB14slides general resources slides general resourcesslides
    General ResourcesSlidesChapter 17: Hierarchical clusteringzip5708KB15slides general resources slides general resourcesslides
    General ResourcesUseful LinksLink to Book's Websitelinkn/aSort Orderuseful links general resources useful links general resources useful links
    Instructor ResourcesSolutionsExercise Solutionspdf2701KB0solutions instructor resources solutions instructor resourcessolutions

    This title has a locked file and access is given only to instructors adopting the textbook for their class. We need to strictly enforce this so that solutions are not made available to students. To gain access to locked resources you need to first log in with your Cambridge account details and then return to this page to submit details of your course so you can be authenticated as an instructor. Click here to log in. If you do not have a Cambridge account you will first need to click here to create an account and then return to this page to be authenticated.


    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.

    If you are having problems accessing these resources please email cflack@cambridge.org

  • Authors

    Christopher D. Manning, Stanford University, California
    fm.author_biographical_note1

    Prabhakar Raghavan, Google, Inc.
    fm.author_biographical_note2

    Hinrich Schütze, Universität Stuttgart
    fm.author_biographical_note3

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