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An $N$-Soft Set Approach to Rough Sets

Authors: José Carlos R. Alcantud; Feng Feng 0003; Ronald R. Yager;

An $N$-Soft Set Approach to Rough Sets

Abstract

The philosophy of soft sets is founded on the fundamental idea of parameterization, while Pawlak?s rough sets put more emphasis on the importance of granulation. As a multi-valued extension of soft sets, the newly emerging concept called N-soft sets can provide a finer granular structure with higher distinguishable power. This study offers a fresh insight into rough set theory from the perspective of N-soft sets. We reveal a close connection between N-soft sets and rough structures of various types. First, we show how the corresponding structures of Pawlak?s rough sets, tolerance rough sets and multigranulation rough sets can be derived from a given N-soft set. Conversely, we investigate the representation of these distinct rough structures using the corresponding notions derived from suitable N-soft sets. The applicability of these theoretical results is highlighted with a case study using real data regarding hotel rating. The established two-way correspondences between N-soft sets and diverse rough structures are constructive, which can bridge the gap between seemingly disconnected disciplines, and hopefully nourish the development of both rough sets and soft sets.

Country
Spain
Related Organizations
Keywords

Multigranulation rough set, Soft set, Rough set, Tolerance rough set, N-soft set, Tolerance relation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
85
Top 1%
Top 10%
Top 1%