Set-theoretic models of granular structures

Authors:
Yiyu Yao;Duoqian Miao;Nan Zhang;Feifei Xu
Affiliations:
Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada;Department of Computer Science and Technology, Tongji University, Shanghai, China;Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada and Department of Computer Science and Technology, Tongji University, Shanghai, China;Department of Computer Science and Technology, Tongji University, Shanghai, China
Venue:
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Year:
2010

Citing 8
Cited 5

Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data
Knowledge Spaces

Knowledge Spaces
On Generalizing Pawlak Approximation Operators

RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Data mining, rough sets and granular computing

Data mining, rough sets and granular computing
Handbook of Granular Computing

Handbook of Granular Computing
Granularity

IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Interpreting concept learning in cognitive informatics and granular computing

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
Rough set approximations in formal concept analysis and knowledge spaces

ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems

Granular structures in graphs

RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Top-down progressive computing

RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Three granular structure models in graphs

RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
Set-theoretic Approaches to Granular Computing

Fundamenta Informaticae - Rough Sets and Knowledge Technology (RSKT 2010)
Comparison of granular computing models in a set-theoretic framework

BI'12 Proceedings of the 2012 international conference on Brain Informatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Granular structure is one of the fundamental concepts in granular computing. Different granular structures reflect multiple aspects of knowledge and information, and depict the different characteristics of data. This paper investigates a family of set-theoretic models of different granular structures. The proposed models are particularly useful for concept formulation and learning. Some of them can be used in formal concept analysis, rough set analysis and knowledge spaces. This unified study of granular structures provides a common framework integrating these theories of granular computing.