Xin Xin
- Information Systems top 1%
- Artificial Intelligence top 2%
- Management Science and Operations Research top 5%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Joemon M. JoseXiangnan HeAlexandros KaratzoglouIoannis ArapakisYoutao ZhangPing GuoJun YangYongfeng Zhang
- Topics
- Recommender Systems and Techniques (38 papers)Topic Modeling (21 papers)Advanced Bandit Algorithms Research (17 papers)
- Journals
- IEEE Transactions on Automatic ControlIEEE Transactions on Knowledge and Data EngineeringApplied Soft Computing
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Xin Xin
76 papers receiving 986 citations
Peers
Comparison fields: 5 of 81
- Information Systems 625
- Artificial Intelligence 593
- Management Science and Operations Research 178
- Computer Vision and Pattern Recognition 169
- Computer Networks and Communications 135
Countries citing papers authored by Xin Xin
This map shows the geographic impact of Xin Xin'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 Xin Xin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Xin more than expected).
Fields of papers citing papers by Xin Xin
This network shows the impact of papers produced by Xin Xin. 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 Xin Xin. The network helps show where Xin Xin may publish in the future.
Co-authorship network of co-authors of Xin Xin
This figure shows the co-authorship network connecting the top 25 collaborators of Xin Xin. A scholar is included among the top collaborators of Xin Xin 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 Xin Xin. Xin Xin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 7 | |
| 10 | 25 | |
| 11 | 8 | |
| 12 | 14 | |
| 13 | 50 | |
| 14 | 11 | |
| 15 | f BGD : Learning Embeddings From Positive Unlabeled Data with BGD. | 14 |
| 16 | 1 | |
| 17 | Cross-domain collaborative filtering with review text | 22 |
| 18 | Re-ranking voting-based answers by discarding user behavior biases | 8 |
| 19 | 3 | |
| 20 | 1 |
About Xin Xin
Xin Xin is a scholar working on Information Systems, Computational Mathematics and Management Science and Operations Research, having authored 82 papers that have together received 1.0k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (38 papers), Topic Modeling (21 papers) and Advanced Bandit Algorithms Research (17 papers). The work is most often cited by research in Information Systems (625 citations), Artificial Intelligence (593 citations) and Management Science and Operations Research (178 citations). Xin Xin has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Joemon M. Jose, Xiangnan He, Alexandros Karatzoglou, Ioannis Arapakis, Youtao Zhang, Ping Guo, Jun Yang, Yongfeng Zhang, Yongdong Zhang and Masahiro Kaneda. Their work appears in journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Knowledge and Data Engineering and Applied Soft Computing.
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.