
Data Mining in Large Sets of Complex Data
Springer (Publisher)
1st Edition
Published on 11. January 2013
Book
Paperback/Softback
XI, 116 pages
978-1-4471-4889-0 (ISBN)
Description
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 / Votes
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)More details
Series
Language
English
Place of publication
London
United Kingdom
Target group
Professional and scholarly
Research
Illustrations
12 s/w Abbildungen, 25 farbige Abbildungen
XI, 116 p. 37 illus., 25 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 8 mm
Weight
207 gr
ISBN-13
978-1-4471-4889-0 (9781447148890)
DOI
10.1007/978-1-4471-4890-6
Schweitzer Classification
Other editions
Additional editions

Robson Leonardo Ferreira Cordeiro | Christos Faloutsos | Caetano Traina Júnior
Data Mining in Large Sets of Complex Data
E-Book
01/2013
1st Edition
Springer
€53.49
Available for download
Content
Preface.- Introduction.- Related Work and Concepts.- Clustering Methods for Moderate-to-High Dimensionality Data.- Halite.- BoW.- QMAS.- Conclusion.