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Springer Mining Very Large Databases with Parallel Processing - Book

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Description

Mining Very Large Databases with Parallel Processing is an interdisciplinary academic text that explores the integration of machine learning-based data mining techniques, relational databases, and parallel processing systems. This Springer publication addresses the practical challenges of large-scale data mining by combining intelligent data mining methodologies with database systems and parallel computing approaches to accelerate and expand the capabilities of data mining algorithms. The book is structured in three comprehensive parts, beginning with an in-depth review of intelligent data mining techniques and progressing through advanced topics that bridge computer science disciplines. Ideal for researchers, computer scientists, and professionals working with massive datasets, this volume provides both theoretical foundations and practical strategies for implementing scalable data mining solutions in enterprise and research environments.

Key Features

Springer publication covering the integration of machine learning-based data mining, relational databases, and parallel processing for large-scale applications.

Three-part structure that begins with a comprehensive review of intelligent data mining techniques and builds toward advanced implementation strategies.

Interdisciplinary approach combining concepts from computer science to address practical challenges in processing and analysing very large databases.

Designed for researchers and professionals seeking to scale data mining algorithms through parallel processing methodologies and database integration.

Academic resource exploring how parallel computing can accelerate traditional data mining operations across enterprise-scale data environments.

Product Specifications

Format
paperback
Domain
Amazon UK
Publication Date
29 October 2012
Listed Since
14 July 2013

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