product iamge

Topics in Rough Set Theory. Current Applications to Granular Computing

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Download
Search on Amazon

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

This book discusses current topics in rough set theory. Since Pawlak’s rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications. Examining various topical issues, including object-oriented rough set models, recommendation systems, decision tables, and granular computing, the book is a valuable resource for students and researchers in the field.

Author(s): Seiki Akama, Yasuo Kudo, Tetsuya Murai
Publisher: Springer
Year: 2020

Language: English
Pages: 208
Tags: Granular Computing, Rough Sets, Rough Set Theory

Front Matter ....Pages i-xv
Introduction (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 1-5
Overview of Rough Set Theory (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 7-60
Object Reduction in Rough Set Theory (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 61-70
Recommendation Method by Direct Setting of Preference Patterns Based on Interrelationship Mining (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 71-79
Rough-Set-Based Interrelationship Mining for Incomplete Decision Tables (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 81-99
A Parallel Computation Method for Heuristic Attribute Reduction Using Reduced Decision Tables (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 101-111
Heuristic Algorithm for Attribute Reduction Based on Classification Ability by Condition Attributes (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 113-127
An Evaluation Method of Relative Reducts Based on Roughness of Partitions (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 129-140
Neighbor Selection for User-Based Collaborative Filtering Using Covering-Based Rough Sets (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 141-159
Granular Computing and Aristotle’s Categorical Syllogism (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 161-172
A Modal Characterization of Visibility and Focus in Granular Reasoning (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 173-185
Directions for Future Work in Rough Set Theory (Seiki Akama, Yasuo Kudo, Tetsuya Murai)....Pages 187-198
Back Matter ....Pages 199-201