Rough Sets: Theoretical Aspects of Reasoning about Data

Author:   Z. Pawlak
Publisher:   Springer
Edition:   1991 ed.
Volume:   9
ISBN:  

9780792314721


Pages:   231
Publication Date:   31 October 1991
Format:   Hardback
Availability:   In Print   Availability explained
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Rough Sets: Theoretical Aspects of Reasoning about Data


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Overview

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.

Full Product Details

Author:   Z. Pawlak
Publisher:   Springer
Imprint:   Springer
Edition:   1991 ed.
Volume:   9
Dimensions:   Width: 15.50cm , Height: 1.50cm , Length: 23.50cm
Weight:   0.549kg
ISBN:  

9780792314721


ISBN 10:   0792314727
Pages:   231
Publication Date:   31 October 1991
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

I. Theoretical Foundations.- 1. Knowledge.- 2. Imprecise Categories, Approximations and Rough Sets.- 3. Reduction of Knowledge.- 4. Dependencies in Knowledge Base.- 5. Knowledge Representation.- 6. Decision Tables.- 7. Reasoning about Knowledge.- II. Applications.- 8. Decision Making.- 9. Data Analysis.- 10. Dissimilarity Analysis.- 11. Switching Circuits.- 12. Machine Learning.

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