Gongshen Liu
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 5%
- Statistical and Nonlinear Physics top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Ru ZhangJianyi LiuFeng ZhuJianhua LiXiaofeng WangShilin WangJianxun LianXing Xie
- Topics
- Topic Modeling (29 papers)Natural Language Processing Techniques (22 papers)Multimodal Machine Learning Applications (10 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Gongshen Liu
83 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 602
- Computer Vision and Pattern Recognition 364
- Information Systems 199
- Statistical and Nonlinear Physics 107
- Computer Networks and Communications 103
Countries citing papers authored by Gongshen Liu
This map shows the geographic impact of Gongshen Liu'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 Gongshen Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gongshen Liu more than expected).
Fields of papers citing papers by Gongshen Liu
This network shows the impact of papers produced by Gongshen Liu. 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 Gongshen Liu. The network helps show where Gongshen Liu may publish in the future.
Co-authorship network of co-authors of Gongshen Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Gongshen Liu. A scholar is included among the top collaborators of Gongshen Liu 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 Gongshen Liu. Gongshen Liu 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 | 9 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 11 | |
| 7 | 14 | |
| 8 | 0 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 20 | |
| 13 | 1 | |
| 14 | 92 | |
| 15 | A Joint Selective Mechanism for Abstractive Sentence Summarization. | 1 |
| 16 | 44 | |
| 17 | 3 | |
| 18 | Research on Prevention Model of Malicious Code in Smart Phone | 1 |
| 19 | Chinese analyzer for search engine-Lucene | 1 |
| 20 | Effective storage structure of inverted index | 0 |
About Gongshen Liu
Gongshen Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 93 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (29 papers), Natural Language Processing Techniques (22 papers) and Multimodal Machine Learning Applications (10 papers). The work is most often cited by research in Artificial Intelligence (602 citations), Computer Vision and Pattern Recognition (364 citations) and Information Systems (199 citations). Gongshen Liu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ru Zhang, Jianyi Liu, Feng Zhu, Jianhua Li, Xiaofeng Wang, Shilin Wang, Jianxun Lian, Xing Xie, Ahmad Mahmoody and Zhuosheng Zhang. Their work appears in journals such as PLoS ONE, Advanced Functional Materials and IEEE Access.
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.