Weiwei Cheng
- Analytical Chemistry top 0.5%
- Spectroscopy and Chemometric Analyses 10
- Animal Science and Zoology top 1%
- Meat and Animal Product Quality 10
- Food Science top 1%
- Polysaccharides Composition and Applications 9
- Artificial Intelligence top 1%
- Topic Modeling 8
- Nutrition and Dietetics top 2%
- Food composition and properties 20
- Microbial Metabolites in Food Biotechnology 15
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- Metal-Organic Frameworks: Synthesis and Applications 14
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- Advanced Chemical Sensor Technologies 9
Weiwei Cheng
106 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 165
- Analytical Chemistry 579
- Animal Science and Zoology 488
- Food Science 859
- Artificial Intelligence 1.1k
- Nutrition and Dietetics 500
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 12 | |
| 4 | 2023 | 35 | |
| 5 | 2023 | 22 | |
| 6 | 2023 | 0 | |
| 7 | 2019 | 30 | |
| 8 | 2019 | 14 | |
| 9 | 2018 | 41 | |
| 10 | 2014 | 49 | |
| 11 | Labelwise versus Pairwise Decomposition in Label Ranking. | 2013 | 8 |
| 12 | Preference-based CBR: general ideas and basic principles | 2013 | 3 |
| 13 | An Exact Algorithm for F-Measure Maximization | 2011 | 58 |
| 14 | Demonstration of a Prototype for a Conversational Companion for Reminiscing about Images | 2010 | 1 |
| 15 | On label dependence in multilabel classification | 2010 | 36 |
| 16 | Graded Multilabel Classification: The Ordinal Case | 2010 | 27 |
| 17 | Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains | 2010 | 243 |
| 18 | Label Ranking Methods based on the Plackett-Luce Model | 2010 | 34 |
| 19 | The senior companion: a semantic web dialogue system | 2009 | 6 |
| 20 | Interactive Ranking of Skylines Using Machine Learning Techniques. | 2007 | 1 |
About Weiwei Cheng
Weiwei Cheng is a scholar working on Analytical Chemistry, Nutrition and Dietetics, Food Science, Inorganic Chemistry and Animal Science and Zoology, having authored 112 papers that have together received 4.0k indexed citations. Recurring topics across this work include Food composition and properties (20 papers), Microbial Metabolites in Food Biotechnology (15 papers), Metal-Organic Frameworks: Synthesis and Applications (14 papers), Spectroscopy and Chemometric Analyses (10 papers), Meat and Animal Product Quality (10 papers), Polysaccharides Composition and Applications (9 papers), Advanced Chemical Sensor Technologies (9 papers) and Topic Modeling (8 papers). The work is most often cited by research in Analytical Chemistry (579 citations), Animal Science and Zoology (488 citations), Food Science (859 citations), Artificial Intelligence (1.1k citations) and Nutrition and Dietetics (500 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, Qingyi Wei and Willem Waegeman. Their work appears in journals such as Food Chemistry, International Journal of Biological Macromolecules, Transition Metal Chemistry, LWT 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.