£107.98

Springer Soft Computing for Data Mining Applications - Vol 190

Name: Springer Soft Computing for Data Mining Applications - Vol 190
Brand: Springer
Price: 107.98 GBP
Availability: InStock

AI & Machine Learning

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Description

Explore the intersection of data science and computational intelligence with Soft Computing for Data Mining Applications. Published by Springer as part of the Studies in Computational Intelligence series, this volume provides a deep look into how soft computing methodologies can be applied to modern data mining challenges. As global data grows exponentially, much of the information collected is imprecise, either implicitly or explicitly. This monograph addresses the complexities of database discovery, focusing on finding noteworthy and unrecognized associations within existing datasets. By utilizing alternate contexts, researchers can uncover additional valuable information that traditional methods might miss. This book serves as a consolidated resource for those studying how to navigate growing data volumes through specialized research. It is a valuable addition to any collection focused on computer science, AI, and machine learning, offering insights into managing and discovering patterns within large-scale, imprecise data environments.

Key Features

Consolidated research work focusing on the integration of soft computing methodologies with data mining techniques.

Provides insight into managing exponential data growth and the challenges of imprecise data sets.

Explores database discovery methods to find unrecognized associations between data items.

Part of the recognized Studies in Computational Intelligence series (Volume 190) by Springer.

Addresses how alternate contexts can reveal additional valuable information within existing databases.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3642001920
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 11 March 2009
Listed Since: 02 January 2009

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Springer Soft Computing for Data Mining Applications - Vol 190

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