Rough sets

1995/11/01 by Zdzislaw Pawlak, Zdzisław Pawlak, Jerzy Grzymala-Busse +4 · 3,215 citations
Computer Science · #Artificial intelligence #Computer science #Data Management and Algorithms #Decision table #Dominance-based rough set approach #Expert system #Fuzzy logic #Granular computing #Knowledge acquisition #Knowledge extraction #Machine learning #Rough Sets and Fuzzy Logic #Rough set #Vagueness

paper · pdf · doi:10.1145/219717.219791

published in Communications of the ACM 38(11), 88-95 (Association for Computing Machinery)

openalex publication_date 1995/11/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/01

Abstract

Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [11, 12], is a new mathematical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.

Cited by

• A Survey of Outlier Detection Methods in Network Anomaly Identification
• Wrappers for feature subset selection
• Solution of the Decision Making Problems using Fuzzy Soft Relations
• Soft matrix theory and its decision making
• Relational Semantics for Nonclassical Logics: Formulas are Relations
• What is the plausibility of probability?(revised 2003, 2015)
• Defining Rough Sets by Extended Logic Programs
• The parameterization reduction of soft sets and its applications
• Automatic Performance Debugging of SPMD Parallel Programs
• Soft Neutrosophic Algebraic Structures and Their Generalization, Vol. 2
• Enriched Interpretation
• Convex and Concave Soft Sets and Some Properties
• Similarity measures of intuitionistic fuzzy soft sets and their decision making
• Rough set theory for topological spaces
• Unifying practical uncertainty representations – I: Generalized p-boxes
• Soft set theory
• An application of soft sets in a decision making problem
• An Experimental Comparison of Three Rough Set Approaches to Missing Attribute Values
• Rough sets theory for multicriteria decision analysis
• An Empirical Analysis of Rough Set Categorical Clustering Techniques. [europepmc]
• Hybrid similarity relation based mutual information for feature selection in intuitionistic fuzzy rough framework and its applications. [europepmc]
• A progressive approach to multi-criteria group decision-making: N-bipolar hypersoft topology perspective. [europepmc]
• Unsupervised attribute reduction based on variable precision weighted neighborhood dependency. [europepmc]

Related

• Machine Learning via rough mereology
• A Program in Dialectical Rough Set Theory
• Enriched Interpretation
• Rough Set Theory (RST) Data Analysis with R and its Application on Studying Relative Significances of Self-Regulated Learning (SRL) Strategies of Gifted Students
• The Evolution of Rough Sets 1970s-1981