Kai Gao
- Artificial Intelligence top 5%
- Experimental and Cognitive Psychology top 10%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Signal Processing
- Topics
- Sentiment Analysis and Opinion Mining (14 papers)Web Data Mining and Analysis (13 papers)Advanced Text Analysis Techniques (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsKnowledge-Based Systems
- Partner nations
- China
In The Last Decade
Kai Gao
43 papers receiving 442 citations
Peers
Comparison fields: 5 of 63
- Artificial Intelligence 382
- Experimental and Cognitive Psychology 71
- Computer Vision and Pattern Recognition 66
- Information Systems 51
- Signal Processing 38
Countries citing papers authored by Kai Gao
This map shows the geographic impact of Kai Gao'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 Kai Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Gao more than expected).
Fields of papers citing papers by Kai Gao
This network shows the impact of papers produced by Kai Gao. 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 Kai Gao. The network helps show where Kai Gao may publish in the future.
Co-authorship network of co-authors of Kai Gao
This figure shows the co-authorship network connecting the top 25 collaborators of Kai Gao. A scholar is included among the top collaborators of Kai Gao 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 Kai Gao. Kai Gao 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 | 8 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 26 | |
| 7 | 34 | |
| 8 | 4 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 3 | |
| 12 | Processing natural language based query and context sensitive spelling suggestion in information retrieval | 0 |
| 13 | Modelling on web dynamic incremental crawling and information processing | 1 |
| 14 | 1 | |
| 15 | Discussion on the experiment teaching reform of electronic technique | 0 |
| 16 | 1 | |
| 17 | Dynamic Refresh Strategy for Crawler in Search Engine | 1 |
| 18 | Design and Implementation of Natural Language Understanding for Search Engine | 2 |
| 19 | 0 | |
| 20 | 7 |
About Kai Gao
Kai Gao is a scholar working on Artificial Intelligence, Information Systems and Signal Processing, having authored 48 papers that have together received 452 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (14 papers), Web Data Mining and Analysis (13 papers) and Advanced Text Analysis Techniques (12 papers). The work is most often cited by research in Artificial Intelligence (382 citations), Experimental and Cognitive Psychology (71 citations) and Signal Processing (38 citations). Kai Gao has collaborated with scholars based in China. Frequent co-authors include Hua Xu, Kai-Cheng Yang, Ziqi Yuan, Yuxiang Xie, Yihe Liu, Yongcheng Wang, Morihiko Nakamura, Hao Li, Xiaohan Zhang and Baoquan Zhang. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications 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.