Fei Cai

1.2k total citations
55 papers, 738 citations indexed

About

Fei Cai is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Fei Cai has authored 55 papers receiving a total of 738 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 26 papers in Information Systems and 7 papers in Management Science and Operations Research. Recurrent topics in Fei Cai's work include Topic Modeling (28 papers), Recommender Systems and Techniques (21 papers) and Advanced Graph Neural Networks (17 papers). Fei Cai is often cited by papers focused on Topic Modeling (28 papers), Recommender Systems and Techniques (21 papers) and Advanced Graph Neural Networks (17 papers). Fei Cai collaborates with scholars based in China, Netherlands and United States. Fei Cai's co-authors include Honghui Chen, Wanyu Chen, Maarten de Rijke, Zhiqiang Pan, Chonghao Chen, Pengfei Jiao, Xuejun Hu, Lin Pan, Wenjun Wang and Pengjie Ren and has published in prestigious journals such as PLoS ONE, Scientific Reports and Information Sciences.

In The Last Decade

Fei Cai

45 papers receiving 727 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fei Cai China 16 543 463 116 106 67 55 738
Lucas Drumond Germany 13 534 1.0× 593 1.3× 175 1.5× 149 1.4× 59 0.9× 32 914
Jianxin Ma China 10 448 0.8× 331 0.7× 127 1.1× 82 0.8× 97 1.4× 15 599
Quanyu Dai China 16 622 1.1× 296 0.6× 163 1.4× 111 1.0× 141 2.1× 44 829
Christopher DuBois United States 6 491 0.9× 611 1.3× 249 2.1× 147 1.4× 68 1.0× 10 812
Chanyoung Park South Korea 17 538 1.0× 361 0.8× 147 1.3× 88 0.8× 142 2.1× 52 781
Jianxin Chang China 10 556 1.0× 623 1.3× 179 1.5× 118 1.1× 33 0.5× 17 840
Xiaofei Zhou China 15 532 1.0× 257 0.6× 156 1.3× 109 1.0× 31 0.5× 44 687

Countries citing papers authored by Fei Cai

Since Specialization
Citations

This map shows the geographic impact of Fei Cai'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 Fei Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Cai more than expected).

Fields of papers citing papers by Fei Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fei Cai. 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 Fei Cai. The network helps show where Fei Cai may publish in the future.

Co-authorship network of co-authors of Fei Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Fei Cai. A scholar is included among the top collaborators of Fei Cai 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 Fei Cai. Fei Cai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chen, Wanyu, et al.. (2025). PEARL: A dual-layer graph learning for multimodal recommendation. Information Fusion. 122. 103168–103168.
2.
Pan, Zhiqiang, Honghui Chen, Wanyu Chen, Fei Cai, & Xinwang Liu. (2025). Time-Aware Graph Learning for Link Prediction on Temporal Networks. IEEE Transactions on Neural Networks and Learning Systems. 36(6). 10619–10634.
3.
Li, Guowang, et al.. (2025). A Structure-Feature Dynamic Decoupling GNN architecture for link prediction. Knowledge-Based Systems. 324. 113883–113883.
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5.
Cai, Fei, et al.. (2024). A counterfactual explanation method based on modified group influence function for recommendation. Complex & Intelligent Systems. 10(6). 7631–7643.
6.
Cai, Fei, et al.. (2024). Multilingual Event Causality Identification via Meta-learning with Knowledge. 18–23. 1 indexed citations
7.
Wang, Siyuan, et al.. (2023). MsPrompt: Multi-step prompt learning for debiasing few-shot event detection. Information Processing & Management. 60(6). 103509–103509. 4 indexed citations
8.
Cai, Fei, et al.. (2023). Pairwise contrastive learning for sentence semantic equivalence identification with limited supervision. Knowledge-Based Systems. 272. 110610–110610. 1 indexed citations
9.
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11.
Cai, Fei, et al.. (2023). Self-supervised graph learning with target-adaptive masking for session-based recommendation. Frontiers of Information Technology & Electronic Engineering. 24(1). 73–87. 1 indexed citations
12.
Cai, Fei, et al.. (2022). Service Quality Evaluation Model of Public Living Facilities in a Community. Tehnicki vjesnik - Technical Gazette. 29(5). 2 indexed citations
13.
Cai, Fei, et al.. (2022). AugPrompt: Knowledgeable augmented-trigger prompt for few-shot event classification. Information Processing & Management. 60(4). 103153–103153. 9 indexed citations
14.
Chen, Chonghao, Fei Cai, Xuejun Hu, Wanyu Chen, & Honghui Chen. (2021). HHGN: A Hierarchical Reasoning-based Heterogeneous Graph Neural Network for fact verification. Information Processing & Management. 58(5). 102659–102659. 24 indexed citations
15.
Cai, Fei, et al.. (2020). Link Prediction based on Deep Latent Feature Model by Fusion of Network Hierarchy Information. Tehnicki vjesnik - Technical Gazette. 27(3). 2 indexed citations
16.
Cai, Fei, et al.. (2019). Urban Function Identification Based on POI and Taxi Trajectory Data. 152–156. 10 indexed citations
17.
Jiao, Pengfei, et al.. (2017). Link predication based on matrix factorization by fusion of multi class organizations of the network. Scientific Reports. 7(1). 8937–8937. 14 indexed citations
18.
Wang, Wenjun, Fei Cai, Pengfei Jiao, & Lin Pan. (2016). A perturbation-based framework for link prediction via non-negative matrix factorization. Scientific Reports. 6(1). 38938–38938. 36 indexed citations
19.
Liao, Zhifang, et al.. (2014). A Tripartite Tensor Decomposition Fold-in for Social Tagging. ResearchOnline (Glasgow Caledonian University). 17(4). 363–370. 1 indexed citations
20.
Cai, Fei, Deke Guo, Honghui Chen, & Zhen Shu. (2012). Your Relevance Feedback Is Essential: Enhancing the Learning to Rank Using the Virtual Feature Based Logistic Regression. PLoS ONE. 7(12). e50112–e50112. 1 indexed citations

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.

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