Data Mining in Large Sets of Complex Data

Author:   Robson Leonardo Ferreira Cordeiro ,  Christos Faloutsos ,  Caetano Traina Júnior
Publisher:   Springer London Ltd
Edition:   2013 ed.
ISBN:  

9781447148890


Pages:   116
Publication Date:   11 January 2013
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Data Mining in Large Sets of Complex Data


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Overview

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.

Full Product Details

Author:   Robson Leonardo Ferreira Cordeiro ,  Christos Faloutsos ,  Caetano Traina Júnior
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   2013 ed.
Dimensions:   Width: 15.50cm , Height: 1.30cm , Length: 23.50cm
Weight:   2.058kg
ISBN:  

9781447148890


ISBN 10:   1447148894
Pages:   116
Publication Date:   11 January 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Preface.- Introduction.- Related Work and Concepts.- Clustering Methods for Moderate-to-High Dimensionality Data.- Halite.- BoW.- QMAS.- Conclusion.

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)


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)


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