Guimin Huang
- Artificial Intelligence top 5%
- Experimental and Cognitive Psychology
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Signal Processing
- Co-authors
- Jun LiYa ZhouLan ShuJing JiangHui LiHua JiangJianheng ChenSiyun Liu
- Topics
- Topic Modeling (23 papers)Natural Language Processing Techniques (18 papers)Peer-to-Peer Network Technologies (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaThe Journal of Clinical Endocrinology & MetabolismScientific Reports
In The Last Decade
Guimin Huang
52 papers receiving 328 citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 211
- Experimental and Cognitive Psychology 55
- Information Systems 48
- Management Science and Operations Research 46
- Signal Processing 41
Countries citing papers authored by Guimin Huang
This map shows the geographic impact of Guimin Huang'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 Guimin Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guimin Huang more than expected).
Fields of papers citing papers by Guimin Huang
This network shows the impact of papers produced by Guimin Huang. 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 Guimin Huang. The network helps show where Guimin Huang may publish in the future.
Co-authorship network of co-authors of Guimin Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Guimin Huang. A scholar is included among the top collaborators of Guimin Huang 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 Guimin Huang. Guimin Huang 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 | 0 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 43 | |
| 11 | Sentence-LDA and Deep Learning: A Combined Approach for Implicit Aspect Extraction and Sentiment Analysis | 1 |
| 12 | A Sentiment Classification Approach of Sentences Clustering in Webcast Barrages | 5 |
| 13 | 6 | |
| 14 | 35 | |
| 15 | 10 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | 40 | |
| 20 | 1 |
About Guimin Huang
Guimin Huang is a scholar working on Artificial Intelligence, Computer Networks and Communications and Signal Processing, having authored 61 papers that have together received 344 indexed citations. Recurring topics across this work include Topic Modeling (23 papers), Natural Language Processing Techniques (18 papers) and Peer-to-Peer Network Technologies (12 papers). The work is most often cited by research in Artificial Intelligence (211 citations), Experimental and Cognitive Psychology (55 citations) and Signal Processing (41 citations). Guimin Huang has collaborated with scholars based in China, Sweden and Australia. Frequent co-authors include Jun Li, Ya Zhou, Lan Shu, Jing Jiang, Hui Li, Hua Jiang, Jianheng Chen, Siyun Liu, Hui Li and Xiaowei Zhang. Their work appears in journals such as SHILAP Revista de lepidopterología, The Journal of Clinical Endocrinology & Metabolism and Scientific Reports.
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.