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Springer Foundations and Advances in Data Mining - Springer Volume 180

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Description

This comprehensive volume from Springer addresses the exponential growth of data availability in modern information systems and the critical challenge of extracting meaningful insights from vast datasets. Foundations and Advances in Data Mining (Volume 180 in the Studies in Fuzziness and Soft Computing series) tackles the data-rich yet information-poor problem by combining theoretical foundations with cutting-edge research directions. The carefully edited collection brings together respected data mining theoreticians and practising researchers, offering both established principles and innovative approaches to understanding and processing large-scale information. Essential reading for professionals and academics working in data mining, artificial intelligence, and computational intelligence who need to stay current with both foundational concepts and emerging methodologies in this rapidly evolving field.

Key Features

Part of Springer's Studies in Fuzziness and Soft Computing series (Volume 180), ensuring rigorous academic standards and peer-reviewed content.

Combines theoretical foundations of data mining with practical advances, addressing both established principles and new research directions.

Edited collection featuring contributions from respected data mining theoreticians and experienced researchers in the field.

Focuses on solving the data-rich and information-poor syndrome through comprehensive data treatment and analysis strategies.

Covers contemporary approaches to extracting meaningful insights from exponentially growing datasets in web systems and information technology.

Suitable for researchers, academics, and professionals in AI, machine learning, and computational intelligence disciplines.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
15 September 2005
Listed Since
31 December 2006

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