Rough Sets - Theoretical Aspects of Reasoning about Data (Hardcover, 1991 ed.)

To-date computers are supposed to store and exploit knowledge. At least that is one of the aims of research fields such as Artificial Intelligence and Information Systems. However, the problem is to understand what knowledge means, to find ways of representing knowledge, and to specify automated machineries that can extract useful information from stored knowledge. Knowledge is something people have in their mind, and which they can express through natural language. Knowl edge is acquired not only from books, but also from observations made during experiments; in other words, from data. Changing data into knowledge is not a straightforward task. A set of data is generally disorganized, contains useless details, although it can be incomplete. Knowledge is just the opposite: organized (e.g. laying bare dependencies, or classifications), but expressed by means of a poorer language, i.e. pervaded by imprecision or even vagueness, and assuming a level of granularity. One may say that knowledge is summarized and organized data - at least the kind of knowledge that computers can store."

General

Imprint:	Springer
Country of origin:	Netherlands
Series:	Theory and Decision Library D:, 9
Release date:	October 1991
First published:	1991
Authors:	Z. Pawlak
Dimensions:	235 x 155 x 15mm (L x W x T)
Format:	Hardcover
Pages:	231
Edition:	1991 ed.
ISBN-13:	978-0-7923-1472-1
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	0-7923-1472-7
Barcode:	9780792314721

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