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Mining Very Large Databases with Parallel Processing

  • Book
  • © 2000

Overview

Authors:
  1. Alex A. Freitas

    1. University of Essex, Colchester, UK

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    You can also search for this author in PubMed   Google Scholar

  2. Simon H. Lavington

    1. University of Essex, Colchester, UK

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: Advances in Database Systems (ADBS, volume 9)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xiii
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  2. Introduction

    1. Introduction

      • Alex A. Freitas, Simon H. Lavington
      Pages 1-4

  3. Knowledge Discovery and Data Mining

    1. Front Matter

      Pages 5-5
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    2. Knowledge Discovery Tasks

      • Alex A. Freitas, Simon H. Lavington
      Pages 7-17

    3. Knowledge Discovery Paradigms

      • Alex A. Freitas, Simon H. Lavington
      Pages 19-29

    4. The Knowledge Discovery Process

      • Alex A. Freitas, Simon H. Lavington
      Pages 31-40

    5. Data Mining

      • Alex A. Freitas, Simon H. Lavington
      Pages 41-50

    6. Data Mining Tools

      • Alex A. Freitas, Simon H. Lavington
      Pages 51-57

  4. Parallel Database Systems

    1. Front Matter

      Pages 59-59
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    2. Basic Concepts on Parallel Processing

      • Alex A. Freitas, Simon H. Lavington
      Pages 61-69

    3. Data Parallelism, Control Parallelism, and Related Issues

      • Alex A. Freitas, Simon H. Lavington
      Pages 71-78

    4. Parallel Database Servers

      • Alex A. Freitas, Simon H. Lavington
      Pages 79-86

  5. Parallel Data Mining

    1. Front Matter

      Pages 87-87
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    2. Approaches to Speed Up Data Mining

      • Alex A. Freitas, Simon H. Lavington
      Pages 89-108

    3. Parallel Data Mining without DBMS Facilities

      • Alex A. Freitas, Simon H. Lavington
      Pages 109-142

    4. Parallel Data Mining with DBMS Facilities

      • Alex A. Freitas, Simon H. Lavington
      Pages 143-172

    5. Summary and Some Open Problems

      • Alex A. Freitas, Simon H. Lavington
      Pages 173-179

  6. Back Matter

    Pages 181-208
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Keywords

About this book

Mining Very Large Databases with Parallel Processing addresses the problem of large-scale data mining. It is an interdisciplinary text, describing advances in the integration of three computer science areas, namely `intelligent' (machine learning-based) data mining techniques, relational databases and parallel processing. The basic idea is to use concepts and techniques of the latter two areas - particularly parallel processing - to speed up and scale up data mining algorithms.
The book is divided into three parts. The first part presents a comprehensive review of intelligent data mining techniques such as rule induction, instance-based learning, neural networks and genetic algorithms. Likewise, the second part presents a comprehensive review of parallel processing and parallel databases. Each of these parts includes an overview of commercially-available, state-of-the-art tools. The third part deals with the application of parallel processing to data mining. The emphasis is on finding generic, cost-effective solutions for realistic data volumes. Two parallel computational environments are discussed, the first excluding the use of commercial-strength DBMS, and the second using parallel DBMS servers.
It is assumed that the reader has a knowledge roughly equivalent to a first degree (BSc) in accurate sciences, so that (s)he is reasonably familiar with basic concepts of statistics and computer science.
The primary audience for Mining Very Large Databases with Parallel Processing is industry data miners and practitioners in general, who would like to apply intelligent data mining techniques to large amounts of data. The book will also be of interest to academic researchers and postgraduate students, particularly database researchers, interested in advanced, intelligent database applications, and artificial intelligence researchers interested in industrial, real-world applications of machine learning.

Authors and Affiliations

  • University of Essex, Colchester, UK

    Alex A. Freitas, Simon H. Lavington

Bibliographic Information

  • Book Title: Mining Very Large Databases with Parallel Processing

  • Authors: Alex A. Freitas, Simon H. Lavington

  • Series Title: Advances in Database Systems

  • DOI: https://doi.org/10.1007/978-1-4615-5521-6

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 2000

  • Hardcover ISBN: 978-0-7923-8048-1Published: 30 November 1997

  • Softcover ISBN: 978-1-4613-7523-4Published: 29 October 2012

  • eBook ISBN: 978-1-4615-5521-6Published: 06 December 2012

  • Series ISSN: 1386-2944

  • Edition Number: 1

  • Number of Pages: XIII, 208

  • Topics: Data Structures and Information Theory, Natural Language Processing (NLP)

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