Mining very large databases with parallel processing
Our rough guess is there are 57,000 words in this book.
At a pace averaging 250 words per minute, this book will take 3 hours and 48 minutes to read. With a half hour per day, this will take 8 days to read.
How long will it take you?
This book will take an estimated to read at a reading speed averaging words per minute. With 30 minutes per day, this will take to read.
Enter your reading speedYou can take one of our WPM reading speed tests to find your reading speed.
Create a free account to track your reading progress, build your reading list, and set reading goals.
Author
Contributions
- Lavington, Simon H. - Contributor
Publication
2000 - Springer, Boston, MA, Massachusetts
Language
English
Word Count
57,000 words, Guess
Page Count
228 pages
Physical Format
Electronic resource
Identifiers
- Internet Archiveminingverylarged00frei
- ISBN-101461555213
- ISBN-139781461555216
- OCLC Control Number840285884
- Better World Books9781461555216
and 1 more
- Open LibraryOL27075122M
Classifications
- LCCQA76.9.D35
Description
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.
Subjects
Series Statement
- Kluwer international series on advances in database systems -- 9
Other Editions
- Mining very large databases with parallel processing
Reader Reviews
No reviews yet for this book.
Be the first to share your thoughts!