Knowledge Discovery in Databases

Gregory. Piatetsky

ISBN 10: 0262660709 / ISBN 13: 9780262660709

Published by MIT Press, 1991

About this Item

Ancien livre de bibliothèque. Livre un peu vrillé. Traces d'usure sur la couverture. Traces d'humidité sur les pages. Couverture différente. Edition 1991. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Book slightly twisted. Signs of wear on the cover. Traces of humidity on the pages. Different cover. Edition 1991. Ammareal gives back up to 15% of this item's net price to charity organizations.

Seller Inventory # D-485-850

Bibliographic Details

• Title: Knowledge Discovery in Databases
• Publisher: MIT Press
• Publication Date: 1991
• Language: English
• ISBN 10: 0262660709
• ISBN 13: 9780262660709
• Binding: Softcover
• Condition: Bon

About this title

Synopsis

Knowledge Discovery in Databases brings together current research on the exciting problem of discovering useful and interesting knowledge in databases. It spans many different approaches to discovery, including inductive learning, bayesian statistics, semantic query optimization, knowledge acquisition for expert systems, information theory, and fuzzy 1 sets.The rapid growth in the number and size of databases creates a need for tools and techniques for intelligent data understanding. Relationships and patterns in data may enable a manufacturer to discover the cause of a persistent disk failure or the reason for consumer complaints. But today's databases hide their secrets beneath a cover of overwhelming detail. The task of uncovering these secrets is called discovery in databases. This loosely defined subfield of machine learning is concerned with discovery from large amounts of possible uncertain data. Its techniques range from statistics to the use of domain knowledge to control search.Following an overview of knowledge discovery in databases, thirty technical chapters are grouped in seven parts which cover discovery of quantitative laws, discovery of qualitative laws, using knowledge in discovery, data summarization, domain specific discovery methods, integrated and multi-paradigm systems, and methodology and application issues. An important thread running through the collection is reliance on domain knowledge, starting with general methods and progressing to specialized methods where domain knowledge is built in.

Gregory Piatetski-Shapiro is Senior Member of Technical Staff and Principal Investigator of the Knowledge Discovery Project at GTE Laboratories. William Frawley is Principal Member of Technical Staff at GTE and Principal Investigator of the Learning in Expert Domains Project.

About the Author

Gregory Piatetsky-Shapiro is Senior Member of Technical Staff and Principal Investigator of the Knowledge Discovery Project at GTE Laboratories.