Zihan Lin
- Information Systems top 1%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Management Science and Operations Research top 5%
- Computer Networks and Communications
- Co-authors
- Wayne Xin ZhaoChangxin TianYupeng HouJi-Rong WenXingyu PanYushuo ChenZhichao FengPengfei Wang
- Topics
- Recommender Systems and Techniques (9 papers)Topic Modeling (5 papers)Advanced Graph Neural Networks (5 papers)
- Partner nations
- ChinaUnited States
In The Last Decade
Zihan Lin
26 papers receiving 644 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Information Systems 533
- Artificial Intelligence 459
- Computer Vision and Pattern Recognition 129
- Management Science and Operations Research 102
- Computer Networks and Communications 58
Countries citing papers authored by Zihan Lin
This map shows the geographic impact of Zihan Lin'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 Zihan Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zihan Lin more than expected).
Fields of papers citing papers by Zihan Lin
This network shows the impact of papers produced by Zihan Lin. 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 Zihan Lin. The network helps show where Zihan Lin may publish in the future.
Co-authorship network of co-authors of Zihan Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Zihan Lin. A scholar is included among the top collaborators of Zihan Lin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zihan Lin. Zihan Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 8 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learningbreakdown → | 297 |
| 13 | 18 | |
| 14 | RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithmsbreakdown → | 220 |
| 15 | A Feed-Forward Neural Network Model For The Accurate Prediction Of Diabetes Mellitus | 14 |
| 16 | 6 | |
| 17 | 1 | |
| 18 | 6 | |
| 19 | 4 | |
| 20 | Novel Boosting Frameworks to Improve the Performance of Collaborative Filtering | 8 |
About Zihan Lin
Zihan Lin is a scholar working on Information Systems, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 32 papers that have together received 655 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (9 papers), Topic Modeling (5 papers) and Advanced Graph Neural Networks (5 papers). The work is most often cited by research in Information Systems (533 citations), Artificial Intelligence (459 citations) and Management Science and Operations Research (102 citations). Zihan Lin has collaborated with scholars based in China and United States. Frequent co-authors include Wayne Xin Zhao, Changxin Tian, Yupeng Hou, Ji-Rong Wen, Xingyu Pan, Yushuo Chen, Zhichao Feng, Pengfei Wang, Hui Wang and Yingqian Min. Their work appears in journals such as PLoS ONE, Journal of Hazardous Materials and Geological Society of America Bulletin.
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.