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Mining Very Large Databases with Parallel Processing by Alex A. Freitas, Simon H. Lavington (auth.) is a nonfiction available to read on EtoBox.
What is Mining Very Large Databases with Parallel Processing about?
__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 p
Who reads Mining Very Large Databases with Parallel Processing?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Alex A. Freitas, Simon H. Lavington (auth.)
- Publisher
- Springer US
- Published
- 2000
- Language
- EN
- ISBN
- 9780792380481
- Category
- nonfiction
- Subjects
- Science, Management, Computer Science
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