Kaixiang Mo
Impact in
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing
- Transportation top 10%
- Human Mobility and Location-Based Analysis
Papers in
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- Speech and dialogue systems 3
- Topic Modeling 3
- Advanced Text Analysis Techniques 1
- Machine Learning and ELM 1
- Natural Language Processing Techniques 1
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- Recommender Systems and Techniques 3
- Co-authors
- Qiang Yang (5 shared papers)Erheng Zhong (3 shared papers)Shuangyin Li (3 shared papers)Ben Tan (2 shared papers)Jiajun Li (2 shared papers)Yu Zhang (1 shared paper)Yong Li (1 shared paper)Jie Jiang (1 shared paper)
- Journals
- Pervasive and Mobile Computing (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (4 papers)arXiv (Cornell University) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
In The Last Decade
Kaixiang Mo
8 papers receiving 164 citations
Peers
Comparison fields: 5 of 43
- Computer Science Applications 38
- Transportation 32
- Artificial Intelligence 103
- Information Systems 33
- Management Science and Operations Research 18
Countries citing papers authored by Kaixiang Mo
This map shows the geographic impact of Kaixiang Mo'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 Kaixiang Mo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaixiang Mo more than expected).
Fields of papers citing papers by Kaixiang Mo
This network shows the impact of papers produced by Kaixiang Mo. 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 Kaixiang Mo. The network helps show where Kaixiang Mo may publish in the future.
Co-authors
The 18 scholars most cited alongside Kaixiang Mo, 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 | 2018 | 39 | |
| 2 | 2013 | 37 | |
| 3 | 2013 | 36 | |
| 4 | Image feature learning for cold start problem in display advertising | 2015 | 22 |
| 5 | Report of Task 3: Your Phone Understands You | 2012 | 12 |
| 6 | Personalizing a Dialogue System with Transfer Learning. | 2016 | 9 |
| 7 | 2020 | 9 | |
| 8 | 2020 | 8 |
About Kaixiang Mo
Kaixiang Mo is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Transportation and Social Psychology, having authored 8 papers that have together received 172 indexed citations. Recurring topics across this work include Speech and dialogue systems (3 papers), Recommender Systems and Techniques (3 papers), Topic Modeling (3 papers), Human Mobility and Location-Based Analysis (2 papers), Advanced Text Analysis Techniques (1 paper), Machine Learning and ELM (1 paper), Natural Language Processing Techniques (1 paper) and Face recognition and analysis (1 paper). The work is most often cited by research in Computer Science Applications (38 citations), Transportation (32 citations), Artificial Intelligence (103 citations), Information Systems (33 citations) and Management Science and Operations Research (18 citations). Kaixiang Mo has collaborated with scholars based in Hong Kong and China. Frequent co-authors include Qiang Yang, Erheng Zhong, Shuangyin Li, Ben Tan, Jiajun Li, Yu Zhang, Yong Li, Jie Jiang, Lei Xiao and Yu Zhang. Their work appears in journals such as Pervasive and Mobile Computing, 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.