Hong Yu

4.4k citations
251 papers · 2.7k indexed · h-index 24

Impact in

Papers in

Hong Yu

226 papers receiving 2.6k citations

Peers

Hong Yu
Comparison fields: 5 of 166
  • Computational Theory and Mathematics 917
  • Artificial Intelligence 1.0k
  • Management Science and Operations Research 332
  • Information Systems 563
  • Computer Vision and Pattern Recognition 443
Replace Gang Wang with:
Gang Wang China
Deyun Zhou China
Barnabás Póczos United States
Fábio Gagliardi Cozman Brazil
Zhengtao Yu China
豊 松尾
Mohammad Ghavamzadeh United States
Lu Wang China
Dongbo Xi China
Ricardo J. G. B. Campello Brazil
Hong Yu relative to Gang Wang China Gang Wang's profile →
Citations per field
00.5×4.8×
Gang Wang · 1×
Citations per year

Countries citing papers authored by Hong Yu

Since Specialization
Citations

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

Fields of papers citing papers by Hong Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Hong Yu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hong Yu Line = papers co-authored together Hong Yu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202415
2 202411
3 20242
4 20243
5 20240
6 20242
7 20243
8 20244
9 20240
10 20238
11 202321
12 20237
13 202329
14 20234
15 20229
16 20145
17 20132
18
Assembly Sequence Planning Based on Screening of Priority Rules
20093
19
An Incremental Rule Acquisition Algorithm Based on Rough Set
20050
20
Rough Set Theory Used for Data Mining
20011

About Hong Yu

Hong Yu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computational Theory and Mathematics and Information Systems, having authored 251 papers that have together received 2.7k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (28 papers), Topic Modeling (19 papers), Natural Language Processing Techniques (15 papers), Water Quality Monitoring Technologies (15 papers), Data Mining Algorithms and Applications (12 papers), Text and Document Classification Technologies (12 papers), Face and Expression Recognition (11 papers) and Advanced Graph Neural Networks (11 papers). The work is most often cited by research in Computational Theory and Mathematics (917 citations), Artificial Intelligence (1.0k citations), Management Science and Operations Research (332 citations), Information Systems (563 citations) and Computer Vision and Pattern Recognition (443 citations). Hong Yu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Guoyin Wang, Cong Zhang, Yiyu Yao, Zhan‐Guo Liu, Ma Xiao, Xianhua Zeng, Xiaoling Ji, Shuyin Xia, Xiaoqing Li and Xin Ding. Their work appears in journals such as Information Sciences, Optics Express, International Journal of Machine Learning and Cybernetics, International Journal of Approximate Reasoning and Journal of Intelligent & Fuzzy Systems.

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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