Rough Sets

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Theoretical Aspects of Reasoning about Data

Szerző: Z. Pawlak

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer

Elérhetőség: Beszállítói készleten

Küldés 10-18 napon belül

141 401 Ft

To-date computers are supposed to store and exploit knowledge. At least that is one of the aims of r...

Információk a könyvről

Szerző

Z. Pawlak

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

1991

oldal

231

EAN

9780792314721

ISBN

0792314727

Enbook ID

01393586

Kiadó

Springer

Súly

549

Méretek

155 x 235 x 13

Teljes leírás

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.

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Rough Sets

Theoretical Aspects of Reasoning about Data

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