Chaofeng Sha
- Artificial Intelligence top 5%
- Topic Modeling 8
- Sentiment Analysis and Opinion Mining 5
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- Software System Performance and Reliability 5
- Network Security and Intrusion Detection 4
- Information Systems top 5%
- Software Engineering Research 8
- Recommender Systems and Techniques 4
- Signal Processing top 5%
- Data Management and Algorithms 4
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- Face and Expression Recognition 4
Chaofeng Sha
37 papers receiving 622 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 402
- Statistical and Nonlinear Physics 139
- Computer Networks and Communications 249
- Information Systems 231
- Signal Processing 103
Countries citing papers authored by Chaofeng Sha
This map shows the geographic impact of Chaofeng Sha'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 Chaofeng Sha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaofeng Sha more than expected).
Fields of papers citing papers by Chaofeng Sha
This network shows the impact of papers produced by Chaofeng Sha. 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 Chaofeng Sha. The network helps show where Chaofeng Sha may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chaofeng Sha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 40 | |
| 2 | 2023 | 6 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 12 | |
| 6 | 2022 | 4 | |
| 7 | 2022 | 3 | |
| 8 | 2022 | 14 | |
| 9 | 2018 | 141 | |
| 10 | A framework for recommending relevant and diverse items | 2016 | 27 |
| 11 | 2014 | 4 | |
| 12 | 2014 | 1 | |
| 13 | 2013 | 1 | |
| 14 | 2013 | 2 | |
| 15 | A Semi-Supervised Learning Algorithm from Imbalanced Data Based on KL Divergence | 2010 | 3 |
| 16 | 2008 | 1 | |
| 17 | 2007 | 45 | |
| 18 | 2004 | 11 | |
| 19 | 2003 | 7 | |
| 20 | 2003 | 7 |
About Chaofeng Sha
Chaofeng Sha is a scholar working on Software, Information Systems, Artificial Intelligence, Signal Processing and Computer Networks and Communications, having authored 39 papers that have together received 648 indexed citations. Recurring topics across this work include Software Engineering Research (8 papers), Topic Modeling (8 papers), Sentiment Analysis and Opinion Mining (5 papers), Software System Performance and Reliability (5 papers), Network Security and Intrusion Detection (4 papers), Face and Expression Recognition (4 papers), Recommender Systems and Techniques (4 papers) and Data Management and Algorithms (4 papers). The work is most often cited by research in Artificial Intelligence (402 citations), Statistical and Nonlinear Physics (139 citations), Computer Networks and Communications (249 citations), Information Systems (231 citations) and Signal Processing (103 citations). Chaofeng Sha has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Aoying Zhou, Yanchun Zhang, Xin Huang, Li Ye, Xin Peng, Weining Qian, Jeffrey Xu Yu, Cheqing Jin, Chenxi Zhang and Bo Xu. Their work appears in journals such as Frontiers of Computer Science, Information Sciences, IEEE Transactions on Software Engineering, Knowledge-Based Systems and World Wide Web.
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.