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Cited by 615

The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.

Three-way decision and granular computing

Open access
Yao, Yiyu·2018·International Journal of Approximate Reasoning

Abstract

Abstract Based on results from cognitive science, this paper examines the two fields of three-way decision and granular computing, as well as their interplay. The ideas from one field shed new light on the other field. The integration of the two gives rise to three-way granular computing, that is, thinking, problem solving, and information processing in threes. We discuss a wide sense of three-way decision and propose a trisecting–acting–outcome (TAO) model. We explain fundamental notions of granular computing based on the philosophy of three-way decision as thinking in threes. We discuss a model of three-way granular computing by making use of two particular types of granular structures represented, respectively, by three granules and three levels. We use examples across different disciplines to demonstrate the values of the two types. Our investigation suggests that, in many situations, the power of granular computing is indeed the power of three-way decision, i.e., thinking in threes.

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Crossref · 10.1016/j.ijar.2018.09.005

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Metadata

Authors
Yao, Y.
Venue
International Journal of Approximate Reasoning
Publisher
Elsevier BV
Published
2018-12
Volume
103
Pages
107-123
ISSN
0888-613X (ISSN-L)
OpenAlex
W2892294644
Cited by
615
References
50
FWCI
40.83
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Three-way decision and granular computing. https://app.cochat.ai/papers/10.1016/j.ijar.2018.09.005
The paper
Yao, Y. (2018). Three-way decision and granular computing. International Journal of Approximate Reasoning. https://doi.org/10.1016/j.ijar.2018.09.005

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.