Zhongli Ding
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Molecular Biology
- Topics
- Bayesian Modeling and Causal Inference (7 papers)Semantic Web and Ontologies (6 papers)Biomedical Text Mining and Ontologies (3 papers)
- Journals
- International Journal of Uncertainty Fuzziness and Knowledge-Based SystemsMaryland Shared Open Access Repository (USMAI Consortium)Defense Technical Information Center (DTIC)
- Partner nations
- United States
In The Last Decade
Zhongli Ding
9 papers receiving 175 citations
Peers
Comparison fields: 5 of 38
- Artificial Intelligence 170
- Signal Processing 51
- Information Systems 46
- Computer Vision and Pattern Recognition 37
- Molecular Biology 36
Countries citing papers authored by Zhongli Ding
This map shows the geographic impact of Zhongli Ding'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 Zhongli Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhongli Ding more than expected).
Fields of papers citing papers by Zhongli Ding
This network shows the impact of papers produced by Zhongli Ding. 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 Zhongli Ding. The network helps show where Zhongli Ding may publish in the future.
Co-authorship network of co-authors of Zhongli Ding
This figure shows the co-authorship network connecting the top 25 collaborators of Zhongli Ding. A scholar is included among the top collaborators of Zhongli Ding 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 Zhongli Ding. Zhongli Ding 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 | 1 | |
| 3 | 16 | |
| 4 | A Bayesian Approach to Uncertainty Modelling in OWL Ontology | 25 |
| 5 | 9 | |
| 6 | BayesOWL: A Probabilistic Framework for Semantic Web | 7 |
| 7 | Bayesowl: a probabilistic framework for uncertainty in semantic web | 10 |
| 8 | 134 | |
| 9 | 1 | |
| 10 | 1 |
About Zhongli Ding
Zhongli Ding is a scholar working on Management Science and Operations Research, Artificial Intelligence and Marketing, having authored 10 papers that have together received 206 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (7 papers), Semantic Web and Ontologies (6 papers) and Biomedical Text Mining and Ontologies (3 papers). The work is most often cited by research in Artificial Intelligence (170 citations), Signal Processing (51 citations) and Management Science and Operations Research (36 citations). Zhongli Ding has collaborated with scholars based in United States. Frequent co-authors include Yun Peng, Rong Pan, Yang Yu, Yongmei Shi, H.S. Cho, Li Ding, Boonserm Kulvatunyou, Nenad Ivezic, Albert Jones and Tim Finin. Their work appears in journals such as International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, Maryland Shared Open Access Repository (USMAI Consortium) and Defense Technical Information Center (DTIC).
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.