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SpringerBriefs in Computer Science

Data Mining in Large Sets of Complex Data

Authors: Ferreira Cordeiro, Robson Leonardo, Faloutsos, Christos, Traina Júnior, Caetano

  • Contains a survey on clustering algorithms for moderate-to-high dimensionality data
  • Includes examples of applications in breast cancer diagnosis, region detection in satellite images, assistance to climate change forecast, recommender systems for the Web, and social networks
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eBook $29.99
price for USA
  • ISBN 978-1-4471-4890-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Softcover $39.95
price for USA
  • ISBN 978-1-4471-4889-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

The amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation? Can it be made automatically? Based on the work discussed in this book, the answers to both questions are a sound “yes”, and the results can be obtained in just minutes. In fact, results that used to require days or weeks of hard work from human specialists can now be obtained in minutes with high precision. Data Mining in Large Sets of Complex Data discusses new algorithms that take steps forward from traditional data mining (especially for clustering) by considering large, complex datasets. Usually, other works focus in one aspect, either data size or complexity. This work considers both: it enables mining complex data from high impact applications, such as breast cancer diagnosis, region classification in satellite images, assistance to climate change forecast, recommendation systems for the Web and social networks; the data are large in the Terabyte-scale, not in Giga as usual; and very accurate results are found in just minutes. Thus, it provides a crucial and well timed contribution for allowing the creation of real time applications that deal with Big Data of high complexity in which mining on the fly can make an immeasurable difference, such as supporting cancer diagnosis or detecting deforestation.

Reviews

From the reviews:

“This book is a must-read for all data mining professionals, as it explains new and superior techniques for clustering large datasets of high-dimensional data. It would also be interesting for professionals who work with large volumes of complex data and want real-time information for better decision making.” (Alexis Leon, Computing Reviews, July, 2013)

Table of contents (7 chapters)

  • Introduction

    Cordeiro, Robson L. F. (et al.)

    Pages 1-6

  • Related Work and Concepts

    Cordeiro, Robson L. F. (et al.)

    Pages 7-20

  • Clustering Methods for Moderate-to-High Dimensionality Data

    Cordeiro, Robson L. F. (et al.)

    Pages 21-32

  • Halite

    Cordeiro, Robson L. F. (et al.)

    Pages 33-67

  • BoW

    Cordeiro, Robson L. F. (et al.)

    Pages 69-92

Buy this book

eBook $29.99
price for USA
  • ISBN 978-1-4471-4890-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Softcover $39.95
price for USA
  • ISBN 978-1-4471-4889-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Data Mining in Large Sets of Complex Data
Authors
Series Title
SpringerBriefs in Computer Science
Copyright
2013
Publisher
Springer-Verlag London
Copyright Holder
The Author(s)
eBook ISBN
978-1-4471-4890-6
DOI
10.1007/978-1-4471-4890-6
Softcover ISBN
978-1-4471-4889-0
Series ISSN
2191-5768
Edition Number
1
Number of Pages
XI, 116
Number of Illustrations and Tables
12 b/w illustrations, 25 illustrations in colour
Topics