Transactions on rough sets XXII

Transactions on rough sets XXII

by Peters, James F. Skowron, Andrzej

Type Book
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The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XXII in the series is a continuation of a number of re…

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Title Statements

  • Full title :Transactions on rough sets XXII / James F. Peters, Andrzej Skowron, (eds.).

Summary

The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XXII in the series is a continuation of a number of research streams that have grown out of the seminal work of Zdzislaw Pawlak during the first decade of the 21st century.

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Edition Statements

  • Publication Date:2020

Publication Statements

  • Publisher(s):Springer
  • Place of Publication:Berlin, Germany
  • Language:eng
  • Publication Date:2020

Notes

Includes index.

The Physical Object

  • Description:1 online resource

Edition Identifiers

  • ISBN:9783662627983, 3662627981
  • DOI:10.1007/978-3-662-62798-3
  • oclc:on1227321469
  • LC Classification:QA248
  • Dewey Decimal:511.3/22

Table of Contents

Decision Trees with at Most 19 Vertices for Knowledge Representation -- jj-ROSETTA -- Sequences of Refinements of Rough Sets: Logical and Algebraic Aspects -- A Study of Algebras and Logics of Rough Sets based on Classical and Generalized Approximation Spaces -- Similarity-based Rough Sets and its Applications in Data Mining.

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Subjects

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