Yuzhong Qu
- Artificial Intelligence top 0.5%
- Information Systems top 0.5%
- Management Science and Operations Research top 0.5%
- Computer Networks and Communications top 2%
- Molecular Biology
- Topics
- Semantic Web and Ontologies (65 papers)Topic Modeling (31 papers)Data Quality and Management (31 papers)
- Journals
- Physics Letters AIEEE Transactions on Neural Networks and Learning SystemsIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Yuzhong Qu
98 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 2.2k
- Information Systems 849
- Management Science and Operations Research 777
- Computer Networks and Communications 731
- Molecular Biology 358
Countries citing papers authored by Yuzhong Qu
This map shows the geographic impact of Yuzhong Qu'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 Yuzhong Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuzhong Qu more than expected).
Fields of papers citing papers by Yuzhong Qu
This network shows the impact of papers produced by Yuzhong Qu. 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 Yuzhong Qu. The network helps show where Yuzhong Qu may publish in the future.
Co-authorship network of co-authors of Yuzhong Qu
This figure shows the co-authorship network connecting the top 25 collaborators of Yuzhong Qu. A scholar is included among the top collaborators of Yuzhong Qu 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 Yuzhong Qu. Yuzhong Qu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 17 | |
| 7 | ESSTER at the EYRE 2020 Entity Summarization Task. | 3 |
| 8 | 28 | |
| 9 | Reading Comprehension with Graph-based Temporal-Casual Reasoning | 8 |
| 10 | njuLink: results for instance matching at OAEI 2017. | 1 |
| 11 | HIEDS: a generic and efficient approach to hierarchical dataset summarization | 6 |
| 12 | Taking up the gaokao challenge: an information retrieval approach | 11 |
| 13 | RelClus: clustering-based relationship search | 1 |
| 14 | 11 | |
| 15 | 55 | |
| 16 | 3 | |
| 17 | Design and Implementation of Ontology-based Information Processing System | 0 |
| 18 | 14 | |
| 19 | A Predicate-Ordered Sort-Ordered Logic for RDFS. | 2 |
| 20 | 1 |
About Yuzhong Qu
Yuzhong Qu is a scholar working on Artificial Intelligence, Management Science and Operations Research and Information Systems, having authored 106 papers that have together received 2.6k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (65 papers), Topic Modeling (31 papers) and Data Quality and Management (31 papers). The work is most often cited by research in Artificial Intelligence (2.2k citations), Management Science and Operations Research (777 citations) and Information Systems (849 citations). Yuzhong Qu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Wei Hu, Gong Cheng, Zequn Sun, Qinghe Zhang, Jinde Cao, De-Shuang Huang, He Huang, Muhao Chen, Han‐Xiong Li and Weiyi Ge. Their work appears in journals such as Physics Letters A, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Knowledge and Data Engineering.
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.