Outlier detection for set-valued data based on rough set theory and granular computing-Reference-Cited by-同舟云学术

Outlier detection for set-valued data based on rough set theory and granular computing

Published:2022-10-17 Issue: Volume: Page:1-29
ISSN:0308-1079
Container-title:International Journal of General Systems
language:en
Short-container-title:International Journal of General Systems

Author:

Lin Hai¹,Li Zhaowen²

Affiliation:

1. College of Mathematics and Information Science, Guangxi University, Nanning, Guangxi, People's Republic of China

2. Key Laboratory of Complex System Optimization and Big Data Processing in Department of Guangxi Education, Yulin Normal University, Yulin, Guangxi, People's Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangxi

Guangxi University for Nationalities

Special Scientific Research Project of Young Innovative Talents in Guangxi

Publisher

Informa UK Limited

Subject

Computer Science Applications,Modeling and Simulation,Information Systems,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/03081079.2022.2132491

Reference50 articles.

1. Aggarwal, C. C., and P. S. Yu. 2001. “Outlier Detection for High Dimensional Data.” In Proceedings of the 2001 ACM SIGMOD International Conference on Management of Data, 37–46.

2. Rough Sets, Kernel Set, and Spatiotemporal Outlier Detection

3. A Rough-Set-Based Incremental Approach for Updating Approximations under Dynamic Maintenance Environments

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Outlier detection method based on improved DPC algorithm and centrifugal factor;Information Sciences;2024-11

2. Outlier detection for heterogeneous data via fuzzy β covering;Expert Systems with Applications;2024-10

3. Unraveling the propagation dynamics of passenger congestion in public transportation systems using big smart card data;International Journal of General Systems;2024-07-30

4. Outlier detection for incomplete real-valued data via information entropy and class-consistent technology;Applied Intelligence;2024-04

5. A new unsupervised outlier detection method;Journal of Intelligent & Fuzzy Systems;2024-01-10