Keping Yang
Impact in
- Information Systems top 2%
- Recommender Systems and Techniques
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
-
- Recommender Systems and Techniques 10
- Web Data Mining and Analysis 3
-
- Sentiment Analysis and Opinion Mining 4
- Text and Document Classification Technologies 3
- Advanced Graph Neural Networks 3
- Topic Modeling 2
- Co-authors
- Quan Lin (7 shared papers)Hong Wen (6 shared papers)Fuyu Lv (2 shared papers)Ningxia Wang (1 shared paper)Quan Yuan (1 shared paper)Li Chen (1 shared paper)Fei Sun (1 shared paper)Wilfred Ng (1 shared paper)
- Journals
- Pattern Recognition (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (1 paper)arXiv (Cornell University) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (1 paper)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Keping Yang
15 papers receiving 399 citations
Peers
Comparison fields: 5 of 59
- Information Systems 286
- Artificial Intelligence 267
- Management Science and Operations Research 89
- Computer Vision and Pattern Recognition 90
- Marketing 35
Countries citing papers authored by Keping Yang
This map shows the geographic impact of Keping Yang'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 Keping Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keping Yang more than expected).
Fields of papers citing papers by Keping Yang
This network shows the impact of papers produced by Keping Yang. 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 Keping Yang. The network helps show where Keping Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Keping Yang, 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 | 2019 | 88 | |
| 2 | 2019 | 75 | |
| 3 | 2020 | 65 | |
| 4 | 2020 | 43 | |
| 5 | 2021 | 33 | |
| 6 | 2022 | 31 | |
| 7 | 2019 | 26 | |
| 8 | 2020 | 16 | |
| 9 | 2021 | 14 | |
| 10 | 2019 | 9 | |
| 11 | 2022 | 9 | |
| 12 | 2021 | 7 | |
| 13 | Conversion Rate Prediction via Post-Click Behaviour Modeling | 2019 | 2 |
| 14 | Multi-Level Deep Cascade Trees for Conversion Rate Prediction. | 2018 | 1 |
| 15 | A Causal Perspective to Unbiased Conversion Rate Estimation on Data Missing Not at Random | 2019 | 1 |
| 16 | 2001 | 0 |
About Keping Yang
Keping Yang is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Urban Studies, having authored 16 papers that have together received 420 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (10 papers), Sentiment Analysis and Opinion Mining (4 papers), Text and Document Classification Technologies (3 papers), Advanced Graph Neural Networks (3 papers), Web Data Mining and Analysis (3 papers), Image and Video Quality Assessment (2 papers), Image Retrieval and Classification Techniques (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Information Systems (286 citations), Artificial Intelligence (267 citations), Management Science and Operations Research (89 citations), Computer Vision and Pattern Recognition (90 citations) and Marketing (35 citations). Keping Yang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Quan Lin, Hong Wen, Fuyu Lv, Ningxia Wang, Quan Yuan, Li Chen, Fei Sun, Wilfred Ng, Xiao-Yang Liu and Ramin Ramezani. Their work appears in journals such as Pattern Recognition, Rare & Special e-Zone (The Hong Kong University of Science and Technology), arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
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.