Keyu Liu

1.5k total citations
53 papers, 1.1k citations indexed

About

Keyu Liu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Keyu Liu has authored 53 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Artificial Intelligence, 37 papers in Computational Theory and Mathematics and 24 papers in Information Systems. Recurrent topics in Keyu Liu's work include Rough Sets and Fuzzy Logic (35 papers), Data Mining Algorithms and Applications (22 papers) and Text and Document Classification Technologies (17 papers). Keyu Liu is often cited by papers focused on Rough Sets and Fuzzy Logic (35 papers), Data Mining Algorithms and Applications (22 papers) and Text and Document Classification Technologies (17 papers). Keyu Liu collaborates with scholars based in China, Japan and Canada. Keyu Liu's co-authors include Xibei Yang, Tianrui Li, Hamido Fujita, Yuhua Qian, Dun Liu, Zhong Yuan, Hualong Yu, Xin Yang, Xiangjian Chen and Pengfei Zhang and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Industry Applications.

In The Last Decade

Keyu Liu

48 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Keyu Liu China 19 833 728 467 314 120 53 1.1k
Jinkun Chen China 17 679 0.8× 543 0.7× 398 0.9× 252 0.8× 176 1.5× 31 982
Binbin Sang China 18 690 0.8× 516 0.7× 398 0.9× 149 0.5× 134 1.1× 29 850
Yanyong Huang China 14 407 0.5× 378 0.5× 250 0.5× 171 0.5× 154 1.3× 26 750
Jihong Wan China 17 373 0.4× 494 0.7× 217 0.5× 252 0.8× 53 0.4× 37 773
Can Gao China 16 344 0.4× 394 0.5× 182 0.4× 262 0.8× 117 1.0× 65 748
Guoping Lin China 18 1.1k 1.3× 491 0.7× 496 1.1× 133 0.4× 325 2.7× 39 1.2k
Tingquan Deng China 11 333 0.4× 260 0.4× 105 0.2× 274 0.9× 198 1.6× 57 731
Jarosław Stepaniuk Poland 13 1.1k 1.3× 520 0.7× 464 1.0× 162 0.5× 220 1.8× 40 1.2k
Chun-Ru Dong China 8 137 0.2× 394 0.5× 101 0.2× 164 0.5× 99 0.8× 31 644

Countries citing papers authored by Keyu Liu

Since Specialization
Citations

This map shows the geographic impact of Keyu Liu'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 Keyu Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keyu Liu more than expected).

Fields of papers citing papers by Keyu Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keyu Liu. 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 Keyu Liu. The network helps show where Keyu Liu may publish in the future.

Co-authorship network of co-authors of Keyu Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Keyu Liu. A scholar is included among the top collaborators of Keyu Liu 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 Keyu Liu. Keyu Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yin, Tengyu, Hongmei Chen, Jihong Wan, et al.. (2025). Leveraging Fuzzy Manifold Intra-Class Correlation and Inter-Class Separability for Online Multilabel Streaming Features Analysis. IEEE Transactions on Multimedia. 27. 6933–6948. 1 indexed citations
2.
Cong, Hui, et al.. (2025). Feature-topology cascade perturbation for graph neural network. Engineering Applications of Artificial Intelligence. 152. 110657–110657.
3.
Xu, Suping, Lin Shang, Keyu Liu, et al.. (2025). Margin-Aware Fuzzy Rough Feature Selection: Bridging Uncertainty Characterization and Pattern Classification. IEEE Transactions on Fuzzy Systems. 34(1). 138–151.
4.
Cong, Hui, Qiguo Sun, Xibei Yang, Keyu Liu, & Yuhua Qian. (2024). Enhancing graph convolutional networks with progressive granular ball sampling fusion: A novel approach to efficient and accurate GCN training. Information Sciences. 676. 120831–120831. 6 indexed citations
5.
Wang, Dexian, Tianrui Li, Ping Deng, et al.. (2024). DNSRF: Deep Network-based Semi-NMF Representation Framework. ACM Transactions on Intelligent Systems and Technology. 15(5). 1–20. 9 indexed citations
6.
Li, Tianrui, et al.. (2024). Feature selection for label distribution learning based on neighborhood fuzzy rough sets. Applied Soft Computing. 169. 112542–112542. 4 indexed citations
7.
Ju, Hengrong, Weiping Ding, Keyu Liu, et al.. (2024). BiFuG2-Spark: Bi-Directional Fuzzy Granular-Cabin Parallel Attribute Reduction Accelerator With Granular-Group Collaboration. IEEE Transactions on Fuzzy Systems. 32(8). 4234–4247. 4 indexed citations
8.
Liu, Keyu, et al.. (2024). Semi-supervised feature selection by minimum neighborhood redundancy and maximum neighborhood relevancy. Applied Intelligence. 54(17-18). 7750–7764. 14 indexed citations
9.
Yin, Tengyu, Hongmei Chen, Keyu Liu, et al.. (2024). Feature selection for multilabel classification with missing labels via multi-scale fusion fuzzy uncertainty measures. Pattern Recognition. 154. 110580–110580. 21 indexed citations
10.
Yang, Yan, et al.. (2024). CiteNet: Cross-modal incongruity perception network for multimodal sentiment prediction. Knowledge-Based Systems. 295. 111848–111848. 7 indexed citations
11.
Li, Tianrui, et al.. (2024). Feature Selection for Handling Label Ambiguity Using Weighted Label-Fuzzy Relevancy and Redundancy. IEEE Transactions on Fuzzy Systems. 32(8). 4436–4447. 9 indexed citations
12.
Yin, Tengyu, Hongmei Chen, Zhong Yuan, et al.. (2023). A Robust Multilabel Feature Selection Approach Based on Graph Structure Considering Fuzzy Dependency and Feature Interaction. IEEE Transactions on Fuzzy Systems. 31(12). 4516–4528. 54 indexed citations
13.
Liu, Keyu, et al.. (2023). SemiFREE: Semisupervised Feature Selection With Fuzzy Relevance and Redundancy. IEEE Transactions on Fuzzy Systems. 31(10). 3384–3396. 38 indexed citations
14.
Liu, Keyu, Tianrui Li, Xibei Yang, et al.. (2023). Feature selection in threes: Neighborhood relevancy, redundancy, and granularity interactivity. Applied Soft Computing. 146. 110679–110679. 19 indexed citations
15.
Zhang, Jiadong, Keyu Liu, Xibei Yang, Hengrong Ju, & Suping Xu. (2023). Multi-label learning with Relief-based label-specific feature selection. Applied Intelligence. 53(15). 18517–18530. 10 indexed citations
16.
Liu, Keyu, Tianrui Li, Xibei Yang, Xin Yang, & Dun Liu. (2022). Neighborhood rough set based ensemble feature selection with cross-class sample granulation. Applied Soft Computing. 131. 109747–109747. 13 indexed citations
17.
Zhang, Pengfei, Tianrui Li, Zhong Yuan, et al.. (2022). Heterogeneous Feature Selection Based on Neighborhood Combination Entropy. IEEE Transactions on Neural Networks and Learning Systems. 35(3). 3514–3527. 82 indexed citations
18.
Chen, Yan, Keyu Liu, Jingjing Song, et al.. (2020). Attribute group for attribute reduction. Information Sciences. 535. 64–80. 86 indexed citations
19.
Liu, Keyu, et al.. (2020). Accelerator for supervised neighborhood based attribute reduction. International Journal of Approximate Reasoning. 119. 122–150. 74 indexed citations
20.
Liu, Keyu, Xibei Yang, Hamido Fujita, et al.. (2019). An efficient selector for multi-granularity attribute reduction. Information Sciences. 505. 457–472. 97 indexed citations

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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