Topics in rough set theory: current applications to granular computing
by Akama, Seiki
"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"--Page 4 of cover.
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- Full title :Topics in rough set theory : current applications to granular computing / Seiki Akama, Yasuo Kudo, Tetsuya Murai.
Summary
"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"--Page 4 of cover.
Read More ↓Edition Statements
- Publication Date:©2020
Publication Statements
- Publisher(s):Springer
- Place of Publication:Cham, Switzerland
- Language:eng
- Publication Date:©2020
The Physical Object
- Description:xv, 201 pages : : illustrations ; : 25 cm
Edition Identifiers
- ISBN:3030295656, 9783030295653
- oclc:on1110440211
- LC Classification:QA248
Table of Contents
Introduction -- Overview of rough set theory -- Object reduction in rough set theory -- Recommendation method by direct setting of preference patterns based on interrelationship mining -- Rough-set-based interrelationship mining for incomplete decision tables -- A parallel computation method for heuristic attribute reduction using reduced decision tables -- Heuristic algorithm for attribute reduction based on classification ability by condition attributes -- An evaluation method of relative reducts based on roughness of partitions -- Neighbor selection for user-based collaborative filtering using covering-based rough sets -- Granular computing and Aristotle's categorical syllogism -- A modal characterization of visibility and focus in granular reasoning -- Directions for future work in rough set theory.
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