Rough Sets

Theoretical Aspects of Reasoning about Data

By:

Z. Pawlak

Format:

Hardback

Series:

Theory and Decision Library D:

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Description

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.

Release date NZ

October 31st, 1991

Author

Z. Pawlak

Audiences

Postgraduate, Research & Scholarly
Professional & Vocational

Illustrations

XVI, 231 p.

Pages

231

Series

Theory and Decision Library D:

Dimensions

155x235x15

ISBN-13

9780792314721

Product ID

14241420

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