Donghong Ji
- Artificial Intelligence top 1%
- Molecular Biology
- Management Science and Operations Research top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Topics
- Topic Modeling (68 papers)Natural Language Processing Techniques (52 papers)Advanced Text Analysis Techniques (23 papers)
- Journals
- BioinformaticsPLoS ONEIEEE Access
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Donghong Ji
84 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 1.3k
- Molecular Biology 282
- Management Science and Operations Research 161
- Information Systems 153
- Computer Vision and Pattern Recognition 137
Countries citing papers authored by Donghong Ji
This map shows the geographic impact of Donghong Ji'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 Donghong Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Donghong Ji more than expected).
Fields of papers citing papers by Donghong Ji
This network shows the impact of papers produced by Donghong Ji. 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 Donghong Ji. The network helps show where Donghong Ji may publish in the future.
Co-authorship network of co-authors of Donghong Ji
This figure shows the co-authorship network connecting the top 25 collaborators of Donghong Ji. A scholar is included among the top collaborators of Donghong Ji 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 Donghong Ji. Donghong Ji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 6 | |
| 5 | 17 | |
| 6 | 1 | |
| 7 | 64 | |
| 8 | 12 | |
| 9 | 43 | |
| 10 | 2 | |
| 11 | 7 | |
| 12 | 15 | |
| 13 | 15 | |
| 14 | 5 | |
| 15 | Multi-Document Summarization Based on Event Term Semantic Relation Graph Clustering | 0 |
| 16 | Query-Focused Multi-Document Summarization Using Co-Training Based Semi-Supervised Learning | 1 |
| 17 | Document Re-ranking via Wikipedia Articles for Definition/Biography Type Questions | 1 |
| 18 | Sentence Ordering based on Cluster Adjacency in Multi-Document Summarization | 6 |
| 19 | Overview of the NTCIR-7 ACLIA IR4QA Task | 22 |
| 20 | I2R at NTCIR5. | 1 |
About Donghong Ji
Donghong Ji is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 88 papers that have together received 1.5k indexed citations. Recurring topics across this work include Topic Modeling (68 papers), Natural Language Processing Techniques (52 papers) and Advanced Text Analysis Techniques (23 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Management Science and Operations Research (161 citations) and Health Informatics (13 citations). Donghong Ji has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Yafeng Ren, Hao Fei, Fei Li, Meishan Zhang, Jingye Li, Fei Hao, Chong Teng, Shengqiong Wu, Yue Zhang and Xiaohui Liang. Their work appears in journals such as Bioinformatics, PLoS ONE 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.