Skip to content
Register Sign in Wishlist

Relational Knowledge Discovery

$57.00 (P)

  • Date Published: July 2012
  • availability: Temporarily unavailable - available from TBC
  • format: Paperback
  • isbn: 9780521122047

$ 57.00 (P)
Paperback

Temporarily unavailable - available from TBC
Notify me when available Add to wishlist

Other available formats:
Hardback, eBook


Looking for an examination copy?

If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact collegesales@cambridge.org providing details of the course you are teaching.

Description
Product filter button
Description
Contents
Resources
Courses
About the Authors
  • What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches.

    • Material has been tried and tested in university courses by the author
    • Necessary theoretical background is provided
    • Exercises are interwoven throughout so readers can progress confidently through the book
    Read more

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity

    ×

    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?

    ×

    Product details

    • Date Published: July 2012
    • format: Paperback
    • isbn: 9780521122047
    • length: 280 pages
    • dimensions: 247 x 173 x 15 mm
    • weight: 0.52kg
    • contains: 50 b/w illus. 100 exercises
    • availability: Temporarily unavailable - available from TBC
  • Table of Contents

    1. Introduction
    2. Relational knowledge
    3. From data to hypotheses
    4. Clustering
    5. Information gain
    6. Knowledge and relations
    7. Rough set theory
    8. Inductive logic learning
    9. Ensemble learning
    10. The logic of knowledge
    11. Indexes and bibliography
    Bibliography
    Index.

  • Resources for

    Relational Knowledge Discovery

    M. E. Müller

    General Resources

    Find resources associated with this title

    Type Name Unlocked * Format Size

    Showing of

    Back to top

    *This title has one or more locked files and access is given only to instructors adopting the textbook for their class. We need to enforce this strictly so that solutions are not made available to students. To gain access to locked resources you either need first to sign in or register for an account.


    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 lecturers@cambridge.org

  • Author

    M. E. Müller, Hochschule Bonn-Rhein-Sieg
    M. E. Mueller is a Professor of Computer Science at the Bonn-Rhein-Sieg University of Applied Sciences.

Sign In

Please sign in to access your account

Cancel

Not already registered? Create an account now. ×

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email lecturers@cambridge.org

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×

Find content that relates to you

Join us online

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.

Cancel

Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

×
Please fill in the required fields in your feedback submission.
×