Yuan Ni
About
In The Last Decade
Yuan Ni
52 papers receiving 307 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 150
- Information Systems 66
- Sociology and Political Science 53
- Computer Networks and Communications 46
- Molecular Biology 32
Countries citing papers authored by Yuan Ni
This map shows the geographic impact of Yuan Ni'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 Yuan Ni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuan Ni more than expected).
Fields of papers citing papers by Yuan Ni
This network shows the impact of papers produced by Yuan Ni. 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 Yuan Ni. The network helps show where Yuan Ni may publish in the future.
Co-authorship network of co-authors of Yuan Ni
This figure shows the co-authorship network connecting the top 25 collaborators of Yuan Ni. A scholar is included among the top collaborators of Yuan Ni 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 Yuan Ni. Yuan Ni 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 | 1 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 3 | |
| 9 | 7 | |
| 10 | 5 | |
| 11 | 1 | |
| 12 | 3 | |
| 13 | PASH at TREC 2020 Deep Learning Track: Dense Matching for Nested Ranking. | 1 |
| 14 | A Multiple Models Ensembling Method in TREC Deep Learning. | 1 |
| 15 | 17 | |
| 16 | MeDetect: domain entity annotation in biomedical references using linked open data | 3 |
| 17 | 6 | |
| 18 | UMRR: towards an enterprise-wide web of models | 2 |
| 19 | An empirical analysis of the consuming structure for Chinese urban citizen | 0 |
| 20 | 16 |
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.