article Open AccessTop 1% cited

Rough sets

Communications of the ACM · 1995 · Vol. 38(11) · pp. 88–95

Zdzisław Pawlak✉(Warsaw University of Technology)Jerzy W. Grzymala‐Busse(University of Kansas)Roman Słowiński(Poznań University of Technology)Wojciech Ziarko(University of Regina)

View via DOI Full-text PDF

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.

Rough Sets and Fuzzy Logic Data Management and AlgorithmsRough setVaguenessComputer scienceArtificial intelligenceKnowledge acquisitionGranular computingDominance-based rough set approachDecision tableExpert systemMachine learning

Citations

3,211

FWCI

69.29

field-weighted impact

References

Percentile

100%

vs. same field & year

Citations per year

Cited by

Rough set approach to incomplete information systems