Lichan Hong
Impact in
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- Computer Graphics and Visualization Techniques
- Information Systems top 0.1%
- Recommender Systems and Techniques
Papers in
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- Computer Graphics and Visualization Techniques 16
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- Advanced Vision and Imaging 10
- Advanced Image and Video Retrieval Techniques 10
- Data Visualization and Analytics 7
- Journals
- IEEE Transactions on Visualization and Computer Graphics (3 papers)IEEE Transactions on Nuclear Science (2 papers)Information Visualization (1 paper)IEEE Transactions on Medical Imaging (1 paper)ACM Transactions on Interactive Intelligent Systems (1 paper)
- Partner nations
- United StatesGermanyAustralia
In The Last Decade
Lichan Hong
78 papers receiving 5.6k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Computer Graphics and Computer-Aided Design 477
- Information Systems 2.7k
- Computer Vision and Pattern Recognition 1.8k
- Artificial Intelligence 2.5k
- Communication 508
Countries citing papers authored by Lichan Hong
This map shows the geographic impact of Lichan Hong'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 Lichan Hong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lichan Hong more than expected).
Fields of papers citing papers by Lichan Hong
This network shows the impact of papers produced by Lichan Hong. 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 Lichan Hong. The network helps show where Lichan Hong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Lichan Hong, 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 | 2024 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 6 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 9 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 6 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 4 | |
| 11 | DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems. | 2020 | 5 |
| 12 | Self-supervised Learning for Deep Models in Recommendations. | 2020 | 20 |
| 13 | 2019 | 73 | |
| 14 | 2002 | 92 | |
| 15 | 2002 | 6 | |
| 16 | 1998 | 16 | |
| 17 | 1997 | 35 | |
| 18 | 1996 | 72 | |
| 19 | 1995 | 8 | |
| 20 | 1995 | 23 |
About Lichan Hong
Lichan Hong is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Human-Computer Interaction, Information Systems and Computer Science Applications, having authored 81 papers that have together received 6.0k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (20 papers), Computer Graphics and Visualization Techniques (16 papers), Topic Modeling (10 papers), Advanced Vision and Imaging (10 papers), Advanced Image and Video Retrieval Techniques (10 papers), Advanced Bandit Algorithms Research (10 papers), 3D Shape Modeling and Analysis (8 papers) and Data Visualization and Analytics (7 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (477 citations), Information Systems (2.7k citations), Computer Vision and Pattern Recognition (1.8k citations), Artificial Intelligence (2.5k citations) and Communication (508 citations). Lichan Hong has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include Ed H., Bongwon Suh, Peter Pirolli, Xinyang Yi, Zhe Zhao, Jilin Chen, Arie Kaufman, Vihan Jain, Hemal Shah and Tal Shaked. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Nuclear Science, Information Visualization, IEEE Transactions on Medical Imaging and ACM Transactions on Interactive Intelligent Systems.
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.