Yang Ji
Impact in
- Artificial Intelligence top 5%
- Sentiment Analysis and Opinion Mining
- Imbalanced Data Classification Techniques
- Topic Modeling
- Anomaly Detection Techniques and Applications
Papers in
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- Caching and Content Delivery 22
- Peer-to-Peer Network Technologies 19
- IoT and Edge/Fog Computing 12
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- Topic Modeling 12
- Advanced Graph Neural Networks 11
- Co-authors
- Zhenyu Wu (18 shared papers)Chunhong Zhang (57 shared papers)Michael Pecht (3 shared papers)Xinning Zhu (10 shared papers)Xinyu Wang (1 shared paper)Li Sun (2 shared papers)Zheng Hu (13 shared papers)Ping Zhang (13 shared papers)
- Journals
- IEEE Access (7 papers)Expert Systems with Applications (3 papers)Wireless Personal Communications (3 papers)Sensors (2 papers)Applied Intelligence (2 papers)
- Partner nations
- ChinaUnited StatesFinland
In The Last Decade
Yang Ji
114 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 101
- Medical Laboratory Technology 25
- Artificial Intelligence 488
- Control and Systems Engineering 328
- Applied Psychology 63
- Computer Networks and Communications 291
Countries citing papers authored by Yang Ji
This map shows the geographic impact of Yang Ji'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 Yang Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yang Ji more than expected).
Fields of papers citing papers by Yang Ji
This network shows the impact of papers produced by Yang Ji. 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 Yang Ji. The network helps show where Yang Ji may publish in the future.
Co-authors
The 25 scholars most cited alongside Yang Ji, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 127 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 172 | |
| 2 | 2018 | 103 | |
| 3 | 2022 | 102 | |
| 4 | 2018 | 70 | |
| 5 | 2019 | 62 | |
| 6 | 2019 | 56 | |
| 7 | 2017 | 37 | |
| 8 | 2021 | 34 | |
| 9 | 2024 | 23 | |
| 10 | 2012 | 23 | |
| 11 | 2018 | 23 | |
| 12 | 2019 | 21 | |
| 13 | 2017 | 19 | |
| 14 | 2020 | 19 | |
| 15 | 2010 | 19 | |
| 16 | 2024 | 18 | |
| 17 | 2014 | 16 | |
| 18 | 2013 | 15 | |
| 19 | 2016 | 15 | |
| 20 | 2017 | 14 |
About Yang Ji
Yang Ji is a scholar working on Computer Networks and Communications, Artificial Intelligence, Information Systems, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 127 papers that have together received 1.2k indexed citations. Recurring topics across this work include Caching and Content Delivery (22 papers), Peer-to-Peer Network Technologies (19 papers), Context-Aware Activity Recognition Systems (13 papers), IoT and Edge/Fog Computing (12 papers), Topic Modeling (12 papers), Multimedia Communication and Technology (12 papers), Advanced Graph Neural Networks (11 papers) and Advanced Wireless Network Optimization (11 papers). The work is most often cited by research in Medical Laboratory Technology (25 citations), Artificial Intelligence (488 citations), Control and Systems Engineering (328 citations), Applied Psychology (63 citations) and Computer Networks and Communications (291 citations). Yang Ji has collaborated with scholars based in China, United States and Finland. Frequent co-authors include Zhenyu Wu, Chunhong Zhang, Michael Pecht, Xinning Zhu, Xinyu Wang, Li Sun, Zheng Hu, Ping Zhang, Han Xiao and Cheng Cheng. Their work appears in journals such as IEEE Access, Expert Systems with Applications, Wireless Personal Communications, Sensors and Applied 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.