Kunli Zhang
- Artificial Intelligence top 10%
- Computer Networks and Communications
- Information Systems
- Molecular Biology
- Electrical and Electronic Engineering
- Topics
- Topic Modeling (20 papers)Natural Language Processing Techniques (12 papers)Text and Document Classification Technologies (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessKnowledge-Based Systems
- Partner nations
- China
In The Last Decade
Kunli Zhang
28 papers receiving 160 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 107
- Computer Networks and Communications 30
- Information Systems 24
- Molecular Biology 23
- Electrical and Electronic Engineering 15
Countries citing papers authored by Kunli Zhang
This map shows the geographic impact of Kunli Zhang'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 Kunli Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kunli Zhang more than expected).
Fields of papers citing papers by Kunli Zhang
This network shows the impact of papers produced by Kunli Zhang. 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 Kunli Zhang. The network helps show where Kunli Zhang may publish in the future.
Co-authorship network of co-authors of Kunli Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Kunli Zhang. A scholar is included among the top collaborators of Kunli Zhang 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 Kunli Zhang. Kunli Zhang 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 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | 61 | |
| 12 | Chinese Deep Semantic Representation with Concept and Logic | 1 |
| 13 | 1 | |
| 14 | 20 | |
| 15 | 4 | |
| 16 | 12 | |
| 17 | Automatic recognition research on preposition's usages based on combination of rules and statistics | 0 |
| 18 | Modern Chinese Conjunction Phrase Recognition Based on Usage | 1 |
| 19 | Research on the Chinese Function Word Usage Knowledge Base. | 1 |
| 20 | Studies on the Functional Word Knowledge Base of Modern Chinese | 2 |
About Kunli Zhang
Kunli Zhang is a scholar working on Artificial Intelligence, Health Information Management and Information Systems, having authored 34 papers that have together received 166 indexed citations. Recurring topics across this work include Topic Modeling (20 papers), Natural Language Processing Techniques (12 papers) and Text and Document Classification Technologies (8 papers). The work is most often cited by research in Health Informatics (5 citations), Artificial Intelligence (107 citations) and Health Information Management (12 citations). Kunli Zhang has collaborated with scholars based in China. Frequent co-authors include Yu Song, Lei Zhuang, Hongying Zan, Kun Li, Guoqing Wang, Hongchao Ma, Wang Ming, Shuai Zhang, Yu Song and Kaixiang Li. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Knowledge-Based Systems.
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.