Pipei Huang
Impact in
- Information Systems top 1%
- Recommender Systems and Techniques
- Artificial Intelligence top 2%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
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- Recommender Systems and Techniques 7
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- Text and Document Classification Technologies 3
- Advanced Graph Neural Networks 3
- Sentiment Analysis and Opinion Mining 2
- Machine Learning and ELM 1
- Co-authors
- Huan Zhao (4 shared papers)Dik Lun Lee (3 shared papers)Binqiang Zhao (2 shared papers)Jizhe Wang (1 shared paper)Zhibo Zhang (1 shared paper)Qiwei Chen (1 shared paper)Wenwu Ou (1 shared paper)Wei Li (1 shared paper)
- Journals
- Pattern Recognition Letters (2 papers)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (3 papers)arXiv (Cornell University) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Pipei Huang
10 papers receiving 903 citations
Pipei Huang's Hit Papers
Peers
Comparison fields: 5 of 76
- Information Systems 654
- Artificial Intelligence 549
- Computer Vision and Pattern Recognition 299
- Management Science and Operations Research 120
- Transportation 59
Countries citing papers authored by Pipei Huang
This map shows the geographic impact of Pipei Huang'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 Pipei Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pipei Huang more than expected).
Fields of papers citing papers by Pipei Huang
This network shows the impact of papers produced by Pipei Huang. 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 Pipei Huang. The network helps show where Pipei Huang may publish in the future.
Co-authors
The 25 scholars most cited alongside Pipei Huang, 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 | Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba Hit paper breakdown → | 2018 | 313 |
| 2 | Behavior sequence transformer for e-commerce recommendation in Alibaba Hit paper breakdown → | 2019 | 238 |
| 3 | 2019 | 205 | |
| 4 | 2019 | 119 | |
| 5 | 2011 | 29 | |
| 6 | 2019 | 26 | |
| 7 | 2020 | 15 | |
| 8 | 2010 | 4 | |
| 9 | 2012 | 2 | |
| 10 | Multi-Level Deep Cascade Trees for Conversion Rate Prediction. | 2018 | 1 |
About Pipei Huang
Pipei Huang is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Marketing, having authored 10 papers that have together received 952 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (7 papers), Text and Document Classification Technologies (3 papers), Advanced Graph Neural Networks (3 papers), Caching and Content Delivery (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Machine Learning and ELM (1 paper), Video Surveillance and Tracking Methods (1 paper) and Face and Expression Recognition (1 paper). The work is most often cited by research in Information Systems (654 citations), Artificial Intelligence (549 citations), Computer Vision and Pattern Recognition (299 citations), Management Science and Operations Research (120 citations) and Transportation (59 citations). Pipei Huang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Huan Zhao, Dik Lun Lee, Binqiang Zhao, Jizhe Wang, Zhibo Zhang, Qiwei Chen, Wenwu Ou, Wei Li, Mengmeng Wu and Qiwei Chen. Their work appears in journals such as Pattern Recognition Letters, Rare & Special e-Zone (The Hong Kong University of Science and Technology), arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.