Bo Long
- Computational Mathematics top 5%
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- Complex Network Analysis Techniques 8
- Artificial Intelligence top 2%
- Advanced Clustering Algorithms Research 5
- Topic Modeling 4
- Advanced Graph Neural Networks 4
- Sentiment Analysis and Opinion Mining 3
- Information Systems top 2%
- Web Data Mining and Analysis 3
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- Magnetic Bearings and Levitation Dynamics 3
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- Electric Motor Design and Analysis 3
- Co-authors
- Philip S. YuZhongfei ZhangShuang-Hong YangHongyuan ZhaZhaohui ZhengWu XiaoyunAlex SmolaYi Chang
- Journals
- Optics Communications (1 paper)IEEE Transactions on Circuits and Systems for Video Technology (1 paper)AI Magazine (1 paper)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Bo Long
27 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Computational Mathematics 19
- Statistical and Nonlinear Physics 353
- Artificial Intelligence 756
- Information Systems 309
- Computer Vision and Pattern Recognition 270
Countries citing papers authored by Bo Long
This map shows the geographic impact of Bo Long'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 Bo Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Long more than expected).
Fields of papers citing papers by Bo Long
This network shows the impact of papers produced by Bo Long. 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 Bo Long. The network helps show where Bo Long may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bo Long, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 13 | |
| 4 | 2023 | 0 | |
| 5 | 2023 | 1 | |
| 6 | Graph Neural Networks for Natural Language Processing: A Surveybreakdown → | 2023 | 134 |
| 7 | 2023 | 0 | |
| 8 | 2022 | 10 | |
| 9 | 2022 | 5 | |
| 10 | 2021 | 9 | |
| 11 | 2020 | 58 | |
| 12 | 2020 | 10 | |
| 13 | 2014 | 32 | |
| 14 | 2012 | 75 | |
| 15 | 2010 | 54 | |
| 16 | 2009 | 14 | |
| 17 | Clustering on complex graphs | 2008 | 12 |
| 18 | Graph partitioning based on link distributions | 2007 | 1 |
| 19 | 2006 | 165 | |
| 20 | 1966 | 3 |
About Bo Long
Bo Long is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Energy Engineering and Power Technology, Information Systems and Computer Graphics and Computer-Aided Design, having authored 32 papers that have together received 1.2k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (8 papers), Advanced Clustering Algorithms Research (5 papers), Topic Modeling (4 papers), Advanced Graph Neural Networks (4 papers), Magnetic Bearings and Levitation Dynamics (3 papers), Sentiment Analysis and Opinion Mining (3 papers), Web Data Mining and Analysis (3 papers) and Electric Motor Design and Analysis (3 papers). The work is most often cited by research in Computational Mathematics (19 citations), Statistical and Nonlinear Physics (353 citations), Artificial Intelligence (756 citations), Information Systems (309 citations) and Computer Vision and Pattern Recognition (270 citations). Bo Long has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Philip S. Yu, Zhongfei Zhang, Shuang-Hong Yang, Hongyuan Zha, Zhaohui Zheng, Wu Xiaoyun, Alex Smola, Yi Chang, Xiaojie Guo and Lingfei Wu. Their work appears in journals such as Optics Communications, IEEE Transactions on Circuits and Systems for Video Technology, AI Magazine, International Journal of Electrical Power & Energy Systems and Knowledge and Information 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.