Li Du
Impact in
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- Topic Modeling
- Natural Language Processing Techniques
- Explainable Artificial Intelligence (XAI)
- Advanced Graph Neural Networks
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- Supply Chain and Inventory Management
Papers in
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- Natural Language Processing Techniques 8
- Topic Modeling 8
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- Auction Theory and Applications 7
- Co-authors
- Xiao Ding (9 shared papers)Bing Qin (7 shared papers)Ting Liu (3 shared papers)Ting Liu (2 shared papers)Ana Belén del Río Lanza (1 shared paper)Xiao Ding (1 shared paper)Qiying Hu (3 shared papers)Shuai Zhang (1 shared paper)
In The Last Decade
Li Du
28 papers receiving 152 citations
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 82
- Management Information Systems 20
- Software 8
- Marketing 19
- Management Science and Operations Research 22
Countries citing papers authored by Li Du
This map shows the geographic impact of Li Du'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 Li Du with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Du more than expected).
Fields of papers citing papers by Li Du
This network shows the impact of papers produced by Li Du. 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 Li Du. The network helps show where Li Du may publish in the future.
Co-authors
The 25 scholars most cited alongside Li Du, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 17 | |
| 2 | 2022 | 16 | |
| 3 | 2021 | 16 | |
| 4 | 2020 | 12 | |
| 5 | 2019 | 10 | |
| 6 | 2021 | 9 | |
| 7 | 2015 | 9 | |
| 8 | 2022 | 8 | |
| 9 | 2021 | 7 | |
| 10 | 2024 | 6 | |
| 11 | 2023 | 6 | |
| 12 | 2004 | 6 | |
| 13 | 2022 | 6 | |
| 14 | 2019 | 6 | |
| 15 | Study on bidding strategies in online auctions | 2006 | 3 |
| 16 | 2024 | 3 | |
| 17 | 2010 | 3 | |
| 18 | 2024 | 2 | |
| 19 | 2006 | 2 | |
| 20 | 2021 | 2 |
About Li Du
Li Du is a scholar working on Artificial Intelligence, Management Science and Operations Research, Marketing, Management Information Systems and Information Systems, having authored 28 papers that have together received 158 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Topic Modeling (8 papers), Auction Theory and Applications (7 papers), Consumer Market Behavior and Pricing (6 papers), Supply Chain and Inventory Management (4 papers), Business Process Modeling and Analysis (3 papers), Optimization and Search Problems (2 papers) and Software Reliability and Analysis Research (2 papers). The work is most often cited by research in Artificial Intelligence (82 citations), Management Information Systems (20 citations), Software (8 citations), Marketing (19 citations) and Management Science and Operations Research (22 citations). Li Du has collaborated with scholars based in China, Hong Kong and Ireland. Frequent co-authors include Xiao Ding, Bing Qin, Ting Liu, Ting Liu, Ting Liu, Ana Belén del Río Lanza, Xiao Ding, Qiying Hu, Shuai Zhang and Jiangbin Zhao. Their work appears in journals such as European Journal of Operational Research, Knowledge-Based Systems, Journal of Cloud Computing Advances Systems and Applications, Information Fusion and Journal of Consumer Behaviour.
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.