Zihui Gu
Impact in
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- Topic Modeling
- Natural Language Processing Techniques
- Semantic Web and Ontologies
- Advanced Text Analysis Techniques
- Anomaly Detection Techniques and Applications
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- Software Engineering Research
Papers in
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- Topic Modeling 4
- Natural Language Processing Techniques 2
- Advanced Text Analysis Techniques 1
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- Software Engineering Research 2
- Co-authors
- Nan Tang (3 shared papers)Ju Fan (4 shared papers)Xiaoyong Du (4 shared papers)Lei Cao (2 shared papers)Samuel Madden (2 shared papers)Preslav Nakov (1 shared paper)Xiang Lin (1 shared paper)Yong Ma (1 shared paper)
- Journals
- Proceedings of the VLDB Endowment (1 paper)Asia Pacific Law Review (1 paper)Proceedings of the 2022 International Conference on Management of Data (1 paper)Proceedings of the ACM on Management of Data (1 paper)Project Muse (Johns Hopkins University) (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Zihui Gu
6 papers receiving 53 citations
Peers
Comparison fields: 5 of 16
- Artificial Intelligence 44
- Information Systems 20
- Management Science and Operations Research 11
- Information Systems and Management 4
- Signal Processing 3
Countries citing papers authored by Zihui Gu
This map shows the geographic impact of Zihui Gu'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 Zihui Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zihui Gu more than expected).
Fields of papers citing papers by Zihui Gu
This network shows the impact of papers produced by Zihui Gu. 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 Zihui Gu. The network helps show where Zihui Gu may publish in the future.
Co-authors
The 10 scholars most cited alongside Zihui Gu, 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 | 2023 | 28 | |
| 2 | 2022 | 11 | |
| 3 | 2024 | 9 | |
| 4 | 2022 | 4 | |
| 5 | The Predictors of Pre-Conviction Decisions in China: A Statistical Analysis Based on M City Court | 2019 | 2 |
| 6 | 2017 | 1 |
About Zihui Gu
Zihui Gu is a scholar working on Artificial Intelligence, Information Systems, Sociology and Political Science, General Health Professions and Law, having authored 6 papers that have together received 55 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Software Engineering Research (2 papers), Natural Language Processing Techniques (2 papers), Advanced Text Analysis Techniques (1 paper), Hermeneutics and Narrative Identity (1 paper), Judicial and Constitutional Studies (1 paper), Health, Medicine and Society (1 paper) and Criminal Law and Evidence (1 paper). The work is most often cited by research in Artificial Intelligence (44 citations), Information Systems (20 citations), Management Science and Operations Research (11 citations), Information Systems and Management (4 citations) and Signal Processing (3 citations). Zihui Gu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Nan Tang, Ju Fan, Xiaoyong Du, Lei Cao, Samuel Madden, Preslav Nakov, Xiang Lin, Yong Ma, Meihui Zhang and Cheng Chen. Their work appears in journals such as Proceedings of the VLDB Endowment, Asia Pacific Law Review, Proceedings of the 2022 International Conference on Management of Data, Proceedings of the ACM on Management of Data and Project Muse (Johns Hopkins University).
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.