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Thriving Rough Sets

Overview of attention for book
Cover of 'Thriving Rough Sets'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 The Born and Growing of Chinese Rough Set Community with Help of Professor Zdzisław Pawlak
  3. Altmetric Badge
    Chapter 2 Zdzisław Pawlak as I Saw Him and Remember Him Now
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    Chapter 3 Recent Development of Rough Computing: A Scientometrics View
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    Chapter 4 Rough Sets, Rough Mereology and Uncertainty
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    Chapter 5 Rough Sets in Machine Learning: A Review
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    Chapter 6 Application of Tolerance Rough Sets in Structured and Unstructured Text Categorization: A Survey
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    Chapter 7 Medical Diagnosis: Rough Set View
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    Chapter 8 Rough Set Analysis of Imprecise Classes
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    Chapter 9 Pawlak’s Many Valued Information System, Non-deterministic Information System, and a Proposal of New Topics on Information Incompleteness Toward the Actual Application
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    Chapter 10 From Information Systems to Interactive Information Systems
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    Chapter 11 Back to the Beginnings: Pawlak’s Definitions of the Terms Information System and Rough Set
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    Chapter 12 Knowledge and Consequence in AC Semantics for General Rough Sets
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    Chapter 13 Measuring Soft Roughness of Soft Rough Sets Induced by Covering
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    Chapter 14 Rough Search of Vague Knowledge
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    Chapter 15 Vagueness and Uncertainty: An F-Rough Set Perspective
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    Chapter 16 Directions of Use of the Pawlak’s Approach to Conflict Analysis
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    Chapter 17 Lattice Structure of Variable Precision Rough Sets
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    Chapter 18 Mining for Actionable Knowledge in Tinnitus Datasets
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    Chapter 19 Rough-Granular Computing for Relational Data
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    Chapter 20 The Boosting and Bootstrap Ensembles for the Pair Classifier Based on the Dual Indiscernibility Matrix
Overall attention for this book and its chapters
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Citations

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Title
Thriving Rough Sets
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-54966-8
ISBNs
978-3-31-954966-8, 978-3-31-954965-1
Editors

Guoyin Wang, Andrzej Skowron, Yiyu Yao, Dominik Ślęzak, Lech Polkowski

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 20%
Researcher 2 20%
Student > Ph. D. Student 2 20%
Student > Doctoral Student 1 10%
Student > Master 1 10%
Other 0 0%
Unknown 2 20%
Readers by discipline Count As %
Computer Science 4 40%
Engineering 2 20%
Energy 1 10%
Mathematics 1 10%
Unknown 2 20%