Shanlei Mu
- Information Systems top 2%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Management Science and Operations Research top 10%
- Computer Networks and Communications
- Topics
- Recommender Systems and Techniques (7 papers)Advanced Graph Neural Networks (6 papers)Topic Modeling (4 papers)
- Journals
- ACM Transactions on Information SystemsProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data MiningProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
- Partner nations
- ChinaUnited States
In The Last Decade
Shanlei Mu
7 papers receiving 460 citations
Hit Papers
Peers
Comparison fields: 5 of 32
- Information Systems 414
- Artificial Intelligence 353
- Computer Vision and Pattern Recognition 98
- Management Science and Operations Research 79
- Computer Networks and Communications 31
Countries citing papers authored by Shanlei Mu
This map shows the geographic impact of Shanlei Mu'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 Shanlei Mu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shanlei Mu more than expected).
Fields of papers citing papers by Shanlei Mu
This network shows the impact of papers produced by Shanlei Mu. 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 Shanlei Mu. The network helps show where Shanlei Mu may publish in the future.
Co-authorship network of co-authors of Shanlei Mu
This figure shows the co-authorship network connecting the top 25 collaborators of Shanlei Mu. A scholar is included among the top collaborators of Shanlei Mu 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 Shanlei Mu. Shanlei Mu 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 | 13 | |
| 3 | Towards Universal Sequence Representation Learning for Recommender Systemsbreakdown → | 123 |
| 4 | 68 | |
| 5 | RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithmsbreakdown → | 220 |
| 6 | 19 | |
| 7 | 22 |
About Shanlei Mu
Shanlei Mu is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research, having authored 7 papers that have together received 467 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (7 papers), Advanced Graph Neural Networks (6 papers) and Topic Modeling (4 papers). The work is most often cited by research in Information Systems (414 citations), Artificial Intelligence (353 citations) and Management Science and Operations Research (79 citations). Shanlei Mu has collaborated with scholars based in China and United States. Frequent co-authors include Ji-Rong Wen, Wayne Xin Zhao, Yaliang Li, Yupeng Hou, Bolin Ding, Xingyu Pan, Changxin Tian, Xinyan Fan, Yushuo Chen and Xu Chen. Their work appears in journals such as ACM Transactions on Information Systems, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining and Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
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.