Skip to main content Accessibility help
×
×
Home
Introduction to Information Retrieval
  • This book is no longer available for purchase
  • Cited by 3598
  • Cited by
    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Husain, Mujaffar and Shanker, Udai 2019. Software Engineering. Vol. 731, Issue. , p. 277.

    Zdrojewska, Anna Dutkiewicz, Jakub Jędrzejek, Czesław and Olejnik, Maciej 2019. Cryptology and Network Security. Vol. 11124, Issue. , p. 290.

    Alabi, Tunrayo R. Adebola, Patrick Olusanmi Asfaw, Asrat De Koeyer, David Lopez-Montes, Antonio and Asiedu, Robert 2019. Spatial Multivariate Cluster Analysis for Defining Target Population of Environments in West Africa for Yam Breeding. International Journal of Applied Geospatial Research, Vol. 10, Issue. 3, p. 1.

    Mary, Leena and G, Deekshitha 2019. Searching Speech Databases. p. 13.

    Corallo, Angelo Trono, Anna Fortunato, Laura Pettinato, Francesco and Schina, Laura 2019. Smart Cities and Smart Spaces. p. 1011.

    Paule, Jorge David Gonzalez Sun, Yeran and Thakuriah, Piyushimita 2019. Transportation Analytics in the Era of Big Data. Vol. 4, Issue. , p. 1.

    Bryniarska, Anna 2019. Recent Advances in Soft Computing. Vol. 837, Issue. , p. 233.

    Jambak, Muhammad Ihsan Mohammed, Fathey Hidayati, Novita Efendi, Rusdi and Primartha, Rifkie 2019. Recent Trends in Data Science and Soft Computing. Vol. 843, Issue. , p. 173.

    Bok, Kyoungsoo Noh, Yeonwoo Lim, Jongtae and Yoo, Jaesoo 2019. Hot topic prediction considering influence and expertise in social media. Electronic Commerce Research,

    Wawrzinek, Janus Pinto, José María González Markiewka, Philipp and Balke, Wolf-Tilo 2019. Data Integration in the Life Sciences. Vol. 11371, Issue. , p. 3.

    Rodríguez-Vidal, Javier Gonzalo, Julio Plaza, Laura and Sánchez, Henry Anaya 2019. Automatic detection of influencers in social networks: Authority versus domain signals. Journal of the Association for Information Science and Technology,

    Samantaray, Prabhat Keshari Randhawa, Navjeet Kaur and Pati, Swarna Lata 2019. Computational Intelligence in Data Mining. Vol. 711, Issue. , p. 31.

    Manoharan, S. N. and Soundar, K. Ruba 2019. A Novel Securable Fuzzy Logic Based Ranking Scheme for Document Searching on Outsourced Cloud Data. Wireless Personal Communications,

    Reinhartz-Berger, Iris and Kemelman, Mark 2019. Extracting core requirements for software product lines. Requirements Engineering,

    Randhawa, Navjeet Kaur and Samantaray, Prabhat Keshari 2019. Soft Computing in Data Analytics. Vol. 758, Issue. , p. 361.

    Do, Thanh‐Nghi and Poulet, François 2019. Latent‐lSVM classification of very high‐dimensional and large‐scale multi‐class datasets. Concurrency and Computation: Practice and Experience, Vol. 31, Issue. 2, p. e4224.

    Soares, Victor Hugo Andrade Campello, Ricardo J. G. B. Nourashrafeddin, Seyednaser Milios, Evangelos and Naldi, Murilo Coelho 2019. Combining semantic and term frequency similarities for text clustering. Knowledge and Information Systems,

    Patel, Himadri and Patel, Bankim 2019. Emerging Trends in Expert Applications and Security. Vol. 841, Issue. , p. 667.

    Kumar, Upendra Tripathi, Esha Tripathi, Surya Prakash and Gupta, Kapil Kumar 2019. Design and Implementation of Healthcare Biometric Systems. p. 73.

    Jorrín, Jesús and Buera, Luis 2019. MultiMedia Modeling. Vol. 11295, Issue. , p. 704.

    ×

Book description

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. 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. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Reviews

'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.

'… this book sets a high standard …'

Source: Natural Language Engineering

'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.'

Source: Computational Linguistics

'This book provides what Salton and Van Rijsbergen both failed to achieve … Even more important, unlike some other books in IR, the authors appear to care about making the theory as accessible as possible to the reader, on occasion including short primers to certain topics or choosing to explain difficult concepts using simplified approaches. … its coverage [is] excellent, the quality of writing high and I was surprised how much I learned from reading it. I think the online resources are impressive.'

Source: Natural Language Engineering

Refine List
Actions for selected content:
Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Send to Kindle
  • Send to Dropbox
  • Send to Google Drive
  • Send content to

    To send content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to .

    To send content items to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

    Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

    Find out more about the Kindle Personal Document Service.

    Please be advised that item(s) you selected are not available.
    You are about to send
    ×

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
×

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Book summary page views

Total views: 0 *
Loading metrics...

* Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

Usage data cannot currently be displayed