Degang Chen

9.6k total citations · 2 hit papers
184 papers, 7.5k citations indexed

About

Degang Chen is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Information Systems. According to data from OpenAlex, Degang Chen has authored 184 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 142 papers in Computational Theory and Mathematics, 95 papers in Artificial Intelligence and 67 papers in Information Systems. Recurrent topics in Degang Chen's work include Rough Sets and Fuzzy Logic (136 papers), Data Mining Algorithms and Applications (60 papers) and Multi-Criteria Decision Making (30 papers). Degang Chen is often cited by papers focused on Rough Sets and Fuzzy Logic (136 papers), Data Mining Algorithms and Applications (60 papers) and Multi-Criteria Decision Making (30 papers). Degang Chen collaborates with scholars based in China, Hong Kong and Macao. Degang Chen's co-authors include Eric C.C. Tsang, Qinghua Hu, Xizhao Wang, Changzhong Wang, Daniel Yeung, Yanyan Yang, Wing W. Y. Ng, Suyun Zhao, Jinhai Li and Changlin Mei and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Pattern Recognition.

In The Last Decade

Degang Chen

174 papers receiving 7.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Feature selection in mixed data: A method using a novel fuzzy rough set-based information entropy

2016 273 citations Changlin Mei, Degang Chen et al. profile →
A Fitting Model for Feature Selection With Fuzzy Rough Sets

2016 217 citations Changzhong Wang, Mingwen Shao et al. profile →

Peers

Degang Chen

CTM

AI

IS

MSOR

CVPR

Andrzej Skowron Poland

Weihua Xu China

Yuhua Qian China

Eric C.C. Tsang China

William Zhu China

Dun Liu China

Wojciech Ziarko Canada

Xibei Yang China

Ju‐Sheng Mi China

Jerzy W. Grzymala‐Busse United States

Andrzej Skowron Poland

Degang Chen

6.5k ×1.0

CTM

3.6k ×1.1

AI

3.2k ×1.0

IS

1.7k ×0.8

MSOR

718 ×0.7

CVPR

Citations per year, relative to Degang Chen Degang Chen (= 1×) peers Andrzej Skowron

Countries citing papers authored by Degang Chen

Since Specialization

Citations

This map shows the geographic impact of Degang Chen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Degang Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Degang Chen more than expected).

Fields of papers citing papers by Degang Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Degang Chen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Degang Chen. The network helps show where Degang Chen may publish in the future.

Co-authorship network of co-authors of Degang Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Degang Chen. A scholar is included among the top collaborators of Degang Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Degang Chen. Degang Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Chen, Degang, et al.. (2025). On the Upper Bounds of Number of Linear Regions and Generalization Error of Deep Convolutional Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(6). 5014–5022.

2.

Chen, Degang, et al.. (2024). Single sample-oriented attribute reduction for rule learning with formal concept analysis. Information Sciences. 681. 121243–121243. 1 indexed citations

3.

Yang, Yanyan, et al.. (2024). A two-way accelerator for feature selection using a monotonic fuzzy conditional entropy. Fuzzy Sets and Systems. 483. 108916–108916. 8 indexed citations

4.

Chen, Degang, et al.. (2023). Multi-kernel learning for multi-label classification with local Rademacher complexity. Information Sciences. 647. 119462–119462. 2 indexed citations

5.

Zhang, Junna, Degang Chen, Qiang Yang, et al.. (2023). Proximity ranking-based multimodal differential evolution. Swarm and Evolutionary Computation. 78. 101277–101277. 36 indexed citations

6.

Zhang, Xiaoxia, Degang Chen, Hong Yu, et al.. (2022). Improving nonnegative matrix factorization with advanced graph regularization. Information Sciences. 597. 125–143. 8 indexed citations

7.

Zhang, Haijun, et al.. (2021). Identifying Clickbait with BERT-BiGA Model. Shuju fenxi yu zhishi faxian. 5(6). 126–134. 1 indexed citations

8.

Wang, Changzhong, Yang Huang, Mingwen Shao, Qinghua Hu, & Degang Chen. (2019). Feature Selection Based on Neighborhood Self-Information. IEEE Transactions on Cybernetics. 50(9). 4031–4042. 213 indexed citations

9.

Zhang, Xiao, Changlin Mei, Degang Chen, & Jinhai Li. (2014). Multi-confidence rule acquisition and confidence-preserved attribute reduction in interval-valued decision systems. International Journal of Approximate Reasoning. 55(8). 1787–1804. 34 indexed citations

10.

Chen, Degang, et al.. (2013). Evidence-theory-based numerical algorithms of attribute reduction with neighborhood-covering rough sets. International Journal of Approximate Reasoning. 55(3). 908–923. 60 indexed citations

11.

Chen, Degang. (2012). Refactoring the Credit Evaluation System of C2C E-commerce——Taking Taobao.com as an example.

12.

Hu, Qinghua, Lei Zhang, Degang Chen, Witold Pedrycz, & Daren Yu. (2010). Gaussian kernel based fuzzy rough sets: Model, uncertainty measures and applications. International Journal of Approximate Reasoning. 51(4). 453–471. 184 indexed citations

13.

Wang, Changzhong, Degang Chen, & Liangkuan Zhu. (2009). Homomorphisms between fuzzy information systems. Applied Mathematics Letters. 22(7). 1045–1050. 25 indexed citations

14.

Wang, Changzhong & Degang Chen. (2009). A short note on some properties of rough groups. Computers & Mathematics with Applications. 59(1). 431–436. 22 indexed citations

15.

Tsang, Eric C.C., Degang Chen, & Daniel Yeung. (2008). Approximations and reducts with covering generalized rough sets. Computers & Mathematics with Applications. 56(1). 279–289. 110 indexed citations

16.

Liu, Min, Degang Chen, Cheng Wu, & Hongxing Li. (2006). Reduction method based on a new fuzzy rough set in fuzzy information system and its applications to scheduling problems. Computers & Mathematics with Applications. 51(9-10). 1571–1584. 16 indexed citations

17.

Liu, Min, Degang Chen, Cheng Wu, & Hongxing Li. (2006). Approximation theorem of the fuzzy transform in fuzzy reasoning and its application to the scheduling problem. Computers & Mathematics with Applications. 51(3-4). 515–526. 11 indexed citations

18.

Chen, Degang. (2005). Variable precision rough set model based on general relations. Journal of Lanzhou University. 10 indexed citations

19.

Chen, Degang, Eric C.C. Tsang, Daniel Yeung, & Xizhao Wang. (2005). The parameterization reduction of soft sets and its applications. Computers & Mathematics with Applications. 49(5-6). 757–763. 468 indexed citations

20.

Chen, Degang, Wen‐Xiu Zhang, & Shiji Song. (2003). Rough class on a completely distributive lattice. Tsinghua Science & Technology. 8(2). 181–184.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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