Weiwei Cheng
Impact in
- Analytical Chemistry top 0.5%
- Spectroscopy and Chemometric Analyses
- Artificial Intelligence top 0.5%
- Text and Document Classification Technologies
- Machine Learning and Data Classification
Papers in
-
- Text and Document Classification Technologies 11
- Machine Learning and Data Classification 10
- Topic Modeling 9
- Food Science 21
- Co-authors
- Eyke Hüllermeier (28 shared papers)Da‐Wen Sun (10 shared papers)Krzysztof Dembczyński (8 shared papers)Di Wu (27 shared papers)Hongbin Pu (7 shared papers)Xiaozhi Tang (22 shared papers)Yan Zhang (12 shared papers)Johannes Fürnkranz (3 shared papers)
In The Last Decade
Weiwei Cheng
121 papers receiving 4.8k citations
Weiwei Cheng's Hit Papers
Peers
Comparison fields: 5 of 168
- Analytical Chemistry 608
- Artificial Intelligence 1.7k
- Animal Science and Zoology 495
- Food Science 882
- Nutrition and Dietetics 533
Countries citing papers authored by Weiwei Cheng
This map shows the geographic impact of Weiwei Cheng'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 Weiwei Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiwei Cheng more than expected).
Fields of papers citing papers by Weiwei Cheng
This network shows the impact of papers produced by Weiwei Cheng. 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 Weiwei Cheng. The network helps show where Weiwei Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside Weiwei Cheng, 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 125 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Label ranking by learning pairwise preferences Hit paper breakdown → | 2008 | 387 |
| 2 | Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains | 2010 | 290 |
| 3 | Applications of metal-organic framework (MOF)-based sensors for food safety: Enhancing mechanisms and recent advances Hit paper breakdown → | 2021 | 272 |
| 4 | 2012 | 232 | |
| 5 | 2009 | 214 | |
| 6 | 2016 | 192 | |
| 7 | 2020 | 172 | |
| 8 | 2017 | 148 | |
| 9 | 2020 | 122 | |
| 10 | 2016 | 118 | |
| 11 | 2017 | 116 | |
| 12 | 2016 | 104 | |
| 13 | 2009 | 93 | |
| 14 | 2015 | 92 | |
| 15 | 2016 | 91 | |
| 16 | 2012 | 89 | |
| 17 | 2019 | 86 | |
| 18 | 2022 | 77 | |
| 19 | 2015 | 74 | |
| 20 | 2012 | 74 |
About Weiwei Cheng
Weiwei Cheng is a scholar working on Artificial Intelligence, Food Science, Nutrition and Dietetics, Biomedical Engineering and Analytical Chemistry, having authored 125 papers that have together received 4.9k indexed citations. Recurring topics across this work include Food composition and properties (20 papers), Metal-Organic Frameworks: Synthesis and Applications (14 papers), Microbial Metabolites in Food Biotechnology (14 papers), Text and Document Classification Technologies (11 papers), Spectroscopy and Chemometric Analyses (10 papers), Meat and Animal Product Quality (10 papers), Machine Learning and Data Classification (10 papers) and Topic Modeling (9 papers). The work is most often cited by research in Analytical Chemistry (608 citations), Artificial Intelligence (1.7k citations), Animal Science and Zoology (495 citations), Food Science (882 citations) and Nutrition and Dietetics (533 citations). Weiwei Cheng has collaborated with scholars based in China, Germany and Ireland. Frequent co-authors include Eyke Hüllermeier, Da‐Wen Sun, Krzysztof Dembczyński, Di Wu, Hongbin Pu, Xiaozhi Tang, Yan Zhang, Johannes Fürnkranz, Willem Waegeman and Klaus Brinker. Their work appears in journals such as Food Chemistry, International Journal of Biological Macromolecules, LWT, Transition Metal Chemistry and Machine Learning.
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.