Yingqiang Ge
- Artificial Intelligence top 2%
- Information Systems top 2%
- Management Science and Operations Research top 5%
- Computer Vision and Pattern Recognition top 10%
- Safety Research top 10%
- Topics
- Recommender Systems and Techniques (14 papers)Explainable Artificial Intelligence (XAI) (8 papers)Topic Modeling (8 papers)
- Journals
- Journal of Molecular LiquidsJournal of the Association for Information Science and TechnologyACM Transactions on Intelligent Systems and Technology
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Yingqiang Ge
25 papers receiving 710 citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 519
- Information Systems 451
- Management Science and Operations Research 104
- Computer Vision and Pattern Recognition 100
- Safety Research 58
Countries citing papers authored by Yingqiang Ge
This map shows the geographic impact of Yingqiang Ge'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 Yingqiang Ge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yingqiang Ge more than expected).
Fields of papers citing papers by Yingqiang Ge
This network shows the impact of papers produced by Yingqiang Ge. 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 Yingqiang Ge. The network helps show where Yingqiang Ge may publish in the future.
Co-authorship network of co-authors of Yingqiang Ge
This figure shows the co-authorship network connecting the top 25 collaborators of Yingqiang Ge. A scholar is included among the top collaborators of Yingqiang Ge 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 Yingqiang Ge. Yingqiang Ge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | 17 | |
| 6 | 0 | |
| 7 | 35 | |
| 8 | 15 | |
| 9 | 20 | |
| 10 | 6 | |
| 11 | 46 | |
| 12 | 49 | |
| 13 | 40 | |
| 14 | 9 | |
| 15 | 1 | |
| 16 | Learning causal explanations for recommendation | 5 |
| 17 | 32 | |
| 18 | 85 | |
| 19 | 0 | |
| 20 | 38 |
About Yingqiang Ge
Yingqiang Ge is a scholar working on Information Systems, Safety Research and Artificial Intelligence, having authored 27 papers that have together received 722 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (14 papers), Explainable Artificial Intelligence (XAI) (8 papers) and Topic Modeling (8 papers). The work is most often cited by research in Information Systems (451 citations), Artificial Intelligence (519 citations) and Management Science and Operations Research (104 citations). Yingqiang Ge has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Yongfeng Zhang, Zuohui Fu, Shijie Geng, Shuchang Liu, Yunqi Li, Shuyuan Xu, Juntao Tan, Hanxiong Chen, Gerard de Melo and Zelong Li. Their work appears in journals such as Journal of Molecular Liquids, Journal of the Association for Information Science and Technology and ACM Transactions on Intelligent Systems and Technology.
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.