Xiaolong Jin
- Artificial Intelligence top 0.5%
- Information Systems top 1%
- Management Science and Operations Research top 2%
- Statistical and Nonlinear Physics top 2%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Xueqi ChengYuanzhuo WangHuawei ShenBenjamin W. WahTong ManSaiping GuanJiafeng GuoYantao Jia
- Topics
- Topic Modeling (38 papers)Advanced Graph Neural Networks (32 papers)Natural Language Processing Techniques (13 papers)
- Partner nations
- ChinaUnited KingdomHong Kong
In The Last Decade
Xiaolong Jin
90 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 1.5k
- Information Systems 652
- Management Science and Operations Research 387
- Statistical and Nonlinear Physics 349
- Computer Vision and Pattern Recognition 312
Countries citing papers authored by Xiaolong Jin
This map shows the geographic impact of Xiaolong Jin'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 Xiaolong Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolong Jin more than expected).
Fields of papers citing papers by Xiaolong Jin
This network shows the impact of papers produced by Xiaolong Jin. 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 Xiaolong Jin. The network helps show where Xiaolong Jin may publish in the future.
Co-authorship network of co-authors of Xiaolong Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaolong Jin. A scholar is included among the top collaborators of Xiaolong Jin 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 Xiaolong Jin. Xiaolong Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 50 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 19 | |
| 8 | 5 | |
| 9 | 12 | |
| 10 | 85 | |
| 11 | The Open Knowledge System for TAC KBP 2017. | 0 |
| 12 | Predict anchor links across social networks via an embedding approach | 142 |
| 13 | 9 | |
| 14 | 2 | |
| 15 | Interorganizational cost management in Australian Construction Alliance | 1 |
| 16 | 28 | |
| 17 | 59 | |
| 18 | A Retrospective of Web Information Retrieval and Mining | 1 |
| 19 | 16 | |
| 20 | Autonomy Oriented Computing: From Problem Solving to Complex Systems Modeling (Multiagent Systems, Artificial Societies, and Simulated Organizations) | 12 |
About Xiaolong Jin
Xiaolong Jin is a scholar working on Artificial Intelligence, Management Science and Operations Research and Management Information Systems, having authored 97 papers that have together received 2.5k indexed citations. Recurring topics across this work include Topic Modeling (38 papers), Advanced Graph Neural Networks (32 papers) and Natural Language Processing Techniques (13 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Management Science and Operations Research (387 citations) and Information Systems (652 citations). Xiaolong Jin has collaborated with scholars based in China, United Kingdom and Hong Kong. Frequent co-authors include Xueqi Cheng, Yuanzhuo Wang, Huawei Shen, Benjamin W. Wah, Tong Man, Saiping Guan, Jiafeng Guo, Yantao Jia, Zixuan Li and Geyong Min. Their work appears in journals such as PLoS ONE, IEEE Access and IEEE Transactions on Communications.
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.