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Author Cordeiro, Robson L. F.

Title Data mining in large sets of complex data / Robson L.F. Cordeiro, Christos Faloutsos, Caetano Traina Júnior.

Publication Info. London : Springer, [2013]
©2013

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Location Call No. OPAC Message Status
 Axe Books 24x7 IT E-Book  Electronic Book    ---  Available
Description 1 online resource (xi, 116 pages) : illustrations (some color), color maps.
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
Series SpringerBriefs in computer science, 2191-5768
SpringerBriefs in computer science.
Contents Introduction -- Related Work and Concepts -- Clustering Methods for Moderate-to-High Dimensionality Data -- Halite -- BoW -- QMAS -- Conclusion.
Bibliography Includes bibliographical references.
Summary 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.
Subject Data mining.
COMPUTERS -- Database Management -- Data Mining.
Data mining. (OCoLC)fst00887946
Data Mining.
Computer Science.
Data Mining and Knowledge Discovery.
Database Management.
Indexed Term Computer science.
Database management.
Data mining.
Genre/Form Electronic books.
Added Author Faloutsos, Christos, author.
Traina Júnior, Caetano, author.
Other Form: Print version: 9781299197121
ISBN 9781447148906 (electronic bk.)
1447148908 (electronic bk.)
1447148894
9781299197121
1299197124
9781447148890
Standard No. 10.1007/978-1-4471-4890-6 doi
AU@ 000050590556
DEBSZ 397438486
DKDLA 820120-katalog:000660865
NLGGC 357171608
NZ1 14832960
NZ1 15737486
NZ1 15905163

 
    
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