Gong Cheng
- Artificial Intelligence top 1%
- Information Systems top 1%
- Management Science and Operations Research top 2%
- Molecular Biology
- Computer Networks and Communications top 5%
- Co-authors
- Yuzhong QuWei HuWeiyi GeXiang ZhangD. W. HerrinYawei SunEvgeny KharlamovLingling Zhang
- Topics
- Semantic Web and Ontologies (46 papers)Topic Modeling (27 papers)Data Quality and Management (22 papers)
- Journals
- NatureSHILAP Revista de lepidopterologíaBioresource Technology
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Gong Cheng
101 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 107
- Artificial Intelligence 971
- Information Systems 522
- Management Science and Operations Research 277
- Molecular Biology 235
- Computer Networks and Communications 203
Countries citing papers authored by Gong Cheng
This map shows the geographic impact of Gong Cheng'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 Gong Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gong Cheng more than expected).
Fields of papers citing papers by Gong Cheng
This network shows the impact of papers produced by Gong Cheng. 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 Gong Cheng. The network helps show where Gong Cheng may publish in the future.
Co-authorship network of co-authors of Gong Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Gong Cheng. A scholar is included among the top collaborators of Gong Cheng 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 Gong Cheng. Gong Cheng 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 | 3 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 3 | |
| 9 | 27 | |
| 10 | ESSTER at the EYRE 2020 Entity Summarization Task. | 3 |
| 11 | 4 | |
| 12 | ES-LDA: Entity Summarization using Knowledge-based Topic Modeling | 17 |
| 13 | 55 | |
| 14 | HIEDS: a generic and efficient approach to hierarchical dataset summarization | 6 |
| 15 | Taking up the gaokao challenge: an information retrieval approach | 11 |
| 16 | RelClus: clustering-based relationship search | 1 |
| 17 | Research on Framework of Virtual Simulation System of Nuclear Facilities Decommissioning | 3 |
| 18 | Development of a Network Expert System for Diagnosis and Control of Silkworm Diseases | 1 |
| 19 | 11 | |
| 20 | 3 |
About Gong Cheng
Gong Cheng is a scholar working on Artificial Intelligence, Management Science and Operations Research and Signal Processing, having authored 109 papers that have together received 1.3k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (46 papers), Topic Modeling (27 papers) and Data Quality and Management (22 papers). The work is most often cited by research in Artificial Intelligence (971 citations), Information Systems (522 citations) and Management Science and Operations Research (277 citations). Gong Cheng has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Yuzhong Qu, Wei Hu, Weiyi Ge, Xiang Zhang, D. W. Herrin, Yawei Sun, Evgeny Kharlamov, Lingling Zhang, Honghan Wu and Tingting Zhu. Their work appears in journals such as Nature, SHILAP Revista de lepidopterología and Bioresource Technology.
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.