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Rough Sets

Theoretical Aspects of Reasoning about Data

  • Zdzisław Pawlak

Part of the Theory and Decision Library book series (TDLD, volume 9)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Theoretical Foundations

    1. Zdzisław Pawlak
      Pages 1-8
    2. Zdzisław Pawlak
      Pages 33-44
    3. Zdzisław Pawlak
      Pages 45-50
    4. Zdzisław Pawlak
      Pages 51-67
    5. Zdzisław Pawlak
      Pages 68-80
    6. Zdzisław Pawlak
      Pages 81-115
  3. Applications

    1. Zdzisław Pawlak
      Pages 116-132
    2. Zdzisław Pawlak
      Pages 133-163
    3. Zdzisław Pawlak
      Pages 164-187
    4. Zdzisław Pawlak
      Pages 188-204
    5. Zdzisław Pawlak
      Pages 205-224
  4. Back Matter
    Pages 225-231

About this book

Introduction

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.

Keywords

Equivalence Pattern Recognition algorithms calculus classification cognition control control algorithm knowledge knowledge base knowledge representation learning machine learning semantics

Authors and affiliations

  • Zdzisław Pawlak
    • 1
  1. 1.Institute of Computer ScienceWarsaw University of TechnologyPoland

Bibliographic information