Jin Ye

37 papers receiving 591 citations

Peers

Jin Ye
Comparison fields: 5 of 68
  • Computational Theory and Mathematics 344
  • Management Science and Operations Research 261
  • Artificial Intelligence 233
  • Signal Processing 63
  • Computer Vision and Pattern Recognition 117
Replace Xiaoyan Zhang with:
Xiaoyan Zhang China
Tingquan Deng China
Władysław Homenda Poland
Can Gao China
Ningxin Xie China
Caihui Liu China
Khaled Mellouli Tunisia
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Xingchen Hu China
Jin Ye relative to Xiaoyan Zhang China Xiaoyan Zhang's profile →
Citations per field
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Xiaoyan Zhang · 1×
Citations per year

Countries citing papers authored by Jin Ye

Since Specialization
Citations

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

Fields of papers citing papers by Jin Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jin Ye, 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 Jin Ye Line = papers co-authored together Jin Ye links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021161
2 2020120
3 202142
4 202335
5 202124
6 202223
7 202123
8 202221
9 202221
10 202119
11 202318
12 202316
13 201913
14 20089
15 20207
16
Research on non-functional conditions-based Web services selection in Web services automation
20065
17 20245
18 20085
19 20185
20 20255

About Jin Ye

Jin Ye is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research and Information Systems, having authored 40 papers that have together received 615 indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (16 papers), Multi-Criteria Decision Making (11 papers), Data Mining Algorithms and Applications (8 papers), Advanced Neural Network Applications (3 papers), Multimodal Machine Learning Applications (3 papers), AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Network Traffic and Congestion Control (3 papers). The work is most often cited by research in Computational Theory and Mathematics (344 citations), Management Science and Operations Research (261 citations), Artificial Intelligence (233 citations), Signal Processing (63 citations) and Computer Vision and Pattern Recognition (117 citations). Jin Ye has collaborated with scholars based in China, United States and Vietnam. Frequent co-authors include Jianming Zhan, Weiping Ding, Пэйдэ Лю, Bingzhen Sun, Hamido Fujita, Xiaoli Chu, Xiaoqing Ye, Wenhao Wu, Zhikang Zou and Yingying Li. Their work appears in journals such as Information Sciences, IEEE Transactions on Fuzzy Systems, Expert Systems with Applications, Applied Intelligence and Engineering Applications of Artificial Intelligence.

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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