Fei Chiang
Impact in
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- Data Quality and Management
- Artificial Intelligence top 5%
- Privacy-Preserving Technologies in Data
- Semantic Web and Ontologies
Papers in
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- Data Quality and Management 30
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- Privacy-Preserving Technologies in Data 14
- Semantic Web and Ontologies 10
- Cryptography and Data Security 5
- Advanced Graph Neural Networks 3
- Co-authors
- Renée J. Miller (7 shared papers)Hyun‐Chul Lee (1 shared paper)Oktie Hassanzadeh (1 shared paper)Jaroslaw Szlichta (6 shared papers)Maksims Volkovs (1 shared paper)Frank Wm. Tompa (1 shared paper)Nilesh Bansal (1 shared paper)Divesh Srivastava (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (4 papers)Journal of Data and Information Quality (3 papers)Transfusion (1 paper)Information Systems (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)
- Partner nations
- CanadaUnited StatesChina
In The Last Decade
Fei Chiang
38 papers receiving 769 citations
Peers
Comparison fields: 5 of 69
- Management Science and Operations Research 566
- Artificial Intelligence 481
- Information Systems 317
- Signal Processing 125
- Computer Networks and Communications 213
Countries citing papers authored by Fei Chiang
This map shows the geographic impact of Fei Chiang'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 Fei Chiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Chiang more than expected).
Fields of papers citing papers by Fei Chiang
This network shows the impact of papers produced by Fei Chiang. 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 Fei Chiang. The network helps show where Fei Chiang may publish in the future.
Co-authors
The 25 scholars most cited alongside Fei Chiang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 195 | |
| 2 | 2009 | 153 | |
| 3 | 2014 | 78 | |
| 4 | 2011 | 69 | |
| 5 | 2015 | 67 | |
| 6 | Seeking stable clusters in the blogosphere | 2007 | 52 |
| 7 | 2019 | 27 | |
| 8 | 2021 | 26 | |
| 9 | 2017 | 13 | |
| 10 | 2019 | 12 | |
| 11 | 2018 | 11 | |
| 12 | 2020 | 11 | |
| 13 | Active repair of data quality rules. | 2011 | 10 |
| 14 | 2013 | 9 | |
| 15 | 2017 | 7 | |
| 16 | 2021 | 7 | |
| 17 | 2022 | 6 | |
| 18 | 2016 | 6 | |
| 19 | 2008 | 6 | |
| 20 | 2015 | 5 |
About Fei Chiang
Fei Chiang is a scholar working on Management Science and Operations Research, Artificial Intelligence, Information Systems, Computer Networks and Communications and Signal Processing, having authored 40 papers that have together received 814 indexed citations. Recurring topics across this work include Data Quality and Management (30 papers), Privacy-Preserving Technologies in Data (14 papers), Data Mining Algorithms and Applications (12 papers), Advanced Database Systems and Queries (10 papers), Semantic Web and Ontologies (10 papers), Cryptography and Data Security (5 papers), Data Management and Algorithms (5 papers) and Advanced Graph Neural Networks (3 papers). The work is most often cited by research in Management Science and Operations Research (566 citations), Artificial Intelligence (481 citations), Information Systems (317 citations), Signal Processing (125 citations) and Computer Networks and Communications (213 citations). Fei Chiang has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Renée J. Miller, Hyun‐Chul Lee, Oktie Hassanzadeh, Jaroslaw Szlichta, Maksims Volkovs, Frank Wm. Tompa, Nilesh Bansal, Divesh Srivastava, Nick Koudas and Zheng Zheng. Their work appears in journals such as Proceedings of the VLDB Endowment, Journal of Data and Information Quality, Transfusion, Information 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.