Overview
- Examines all aspects of data abstraction generation using a least number of database scans
- Discusses compressing data through novel lossy and non-lossy schemes
- Proposes schemes for carrying out clustering and classification directly in the compressed domain
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (8 chapters)
Keywords
About this book
Authors and Affiliations
About the authors
Dr. T. Ravindra Babu is a Principal Researcher in the E-Commerce Research Labs at Infosys Ltd., Bangalore, India. Mr. S.V. Subrahmanya is Vice President and Research Fellow at the same organization. Dr. M. Narasimha Murty is a Professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore, India.
Bibliographic Information
Book Title: Compression Schemes for Mining Large Datasets
Book Subtitle: A Machine Learning Perspective
Authors: T. Ravindra Babu, M. Narasimha Murty, S.V. Subrahmanya
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-1-4471-5607-9
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London 2013
Hardcover ISBN: 978-1-4471-5606-2Published: 04 December 2013
Softcover ISBN: 978-1-4471-7055-6Published: 17 September 2016
eBook ISBN: 978-1-4471-5607-9Published: 19 November 2013
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: XVI, 197
Number of Illustrations: 59 b/w illustrations, 3 illustrations in colour
Topics: Pattern Recognition, Data Mining and Knowledge Discovery, Artificial Intelligence