Xuelei Hu
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition
- Molecular Biology
- Signal Processing
- Public Health, Environmental and Occupational Health
- Topics
- Text and Document Classification Technologies (6 papers)Sentiment Analysis and Opinion Mining (5 papers)Opioid Use Disorder Treatment (4 papers)
In The Last Decade
Xuelei Hu
34 papers receiving 404 citations
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 240
- Computer Vision and Pattern Recognition 55
- Molecular Biology 48
- Signal Processing 30
- Public Health, Environmental and Occupational Health 27
Countries citing papers authored by Xuelei Hu
This map shows the geographic impact of Xuelei Hu'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 Xuelei Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xuelei Hu more than expected).
Fields of papers citing papers by Xuelei Hu
This network shows the impact of papers produced by Xuelei Hu. 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 Xuelei Hu. The network helps show where Xuelei Hu may publish in the future.
Co-authorship network of co-authors of Xuelei Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Xuelei Hu. A scholar is included among the top collaborators of Xuelei Hu 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 Xuelei Hu. Xuelei Hu 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 | 0 | |
| 3 | 0 | |
| 4 | 8 | |
| 5 | 12 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 12 | |
| 9 | 8 | |
| 10 | 7 | |
| 11 | 9 | |
| 12 | 5 | |
| 13 | Feature Ensemble Plus Sample Selection: Domain Adaptation for Sentiment Classification (Extended Abstract) | 3 |
| 14 | 6 | |
| 15 | Dual training and dual prediction for polarity classification | 15 |
| 16 | Feature ensemble plus sample selection: domain adaptation for sentiment classification | 3 |
| 17 | Instance selection and instance weighting for cross-domain sentiment classification via PU learning | 23 |
| 18 | 1 | |
| 19 | 3 | |
| 20 | A Comparative Investigation on Model Selection in Binary Factor Analysis. | 2 |
About Xuelei Hu
Xuelei Hu is a scholar working on Geriatrics and Gerontology, Anesthesiology and Pain Medicine and Artificial Intelligence, having authored 40 papers that have together received 425 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (6 papers), Sentiment Analysis and Opinion Mining (5 papers) and Opioid Use Disorder Treatment (4 papers). The work is most often cited by research in Artificial Intelligence (240 citations), Geriatrics and Gerontology (12 citations) and Anesthesiology and Pain Medicine (16 citations). Xuelei Hu has collaborated with scholars based in China, Australia and Hong Kong. Frequent co-authors include Chengqing Zong, Rui Xia, Erik Cambria, Lei Xu, Jianfeng Lu, Bo Yuan, Lian-Tao Wang, Jian Yang, Jason P. Connor and Joemer C Maravilla. Their work appears in journals such as Chemical Engineering Journal, Journal of Materials Chemistry A and Journal of Colloid and Interface Science.
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.