Skip to content
Register Sign in Wishlist
Scientific Data Mining

Scientific Data Mining
A Practical Perspective

$84.00 (P)

  • Date Published: June 2009
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • format: Paperback
  • isbn: 9780898716757

$ 84.00 (P)

This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
Unavailable Add to wishlist

Looking for an examination copy?

This title is not currently available for examination. However, if you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact providing details of the course you are teaching.

Product filter button
About the Authors
  • Technological advances are enabling scientists to collect vast amounts of data in fields such as medicine, remote sensing, astronomy, and high-energy physics. These data arise not only from experiments and observations, but also from computer simulations of complex phenomena. As a result, it has become impractical to manually analyze and understand the data. This book describes how techniques from the multi-disciplinary field of data mining can be used to address the modern problem of data overload in science and engineering domains. Starting with a survey of analysis problems in different applications, it identifies the common themes across these domains and uses them to define an end-to-end process of scientific data mining. This multi-step process includes tasks such as processing the raw image or mesh data to identify objects of interest; extracting relevant features describing the objects; detecting patterns among the objects; and displaying the patterns for validation by the scientists.

    • Brings together techniques from many different disciplines which are useful in the analysis of scientific data
    • Gives the reader an opportunity to benefit from solutions developed in other problem domains by surveying many different science and engineering applications
    • Includes a description of software systems developed for scientific data mining and general guidelines for getting started on the analysis of massive, complex data sets
    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: June 2009
    • format: Paperback
    • isbn: 9780898716757
    • length: 300 pages
    • dimensions: 255 x 178 x 14 mm
    • weight: 0.53kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • Table of Contents

    1. Introduction
    2. Data mining in science and engineering
    3. Common themes in mining scientific data
    4. The scientific data mining process
    5. Reducing the size of the data
    6. Fusing different data modalities
    7. Enhancing image data
    8. Finding objects in the data
    9. Extracting features describing the objects
    10. Reducing the dimension of the data
    11. Finding patterns in the data
    12. Visualizing the data and validating the results
    13. Scientific data mining systems
    14. Lessons learned, challenges, and opportunities

  • Author

    Chandrika Kamath, Lawrence Livermore National Laboratory, California
    Chandrika Kamath is a researcher at Lawrence Livermore National Laboratory, where she is involved in the analysis of data from scientific simulations, observations, and experiments. Her interests include signal and image processing, machine learning, pattern recognition, and statistics, as well as the application of data mining techniques to the solution of practical problems.

Sorry, this resource is locked

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

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 Please see the permission section of the catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×
warning icon

Turn stock notifications on?

You must be signed in to your Cambridge account to turn product stock notifications on or off.

Sign in Create a Cambridge account arrow icon

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.


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.