Authors:
- 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
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (7 chapters)
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Front Matter
About this book
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)Authors and Affiliations
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Computer Science Department - ICMC, University of São Paulo, São Carlos, Brazil
Robson L. F. Cordeiro, Caetano Traina Júnior
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School of Computer Science, Carnegie Mellon University, Pittsburgh, USA
Christos Faloutsos
Bibliographic Information
Book Title: Data Mining in Large Sets of Complex Data
Authors: Robson L. F. Cordeiro, Christos Faloutsos, Caetano Traina Júnior
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-1-4471-4890-6
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s) 2013
Softcover ISBN: 978-1-4471-4889-0Published: 11 January 2013
eBook ISBN: 978-1-4471-4890-6Published: 11 January 2013
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XI, 116
Number of Illustrations: 12 b/w illustrations, 25 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Database Management