Tong Chen

6.7k total citations · 4 hit papers
158 papers, 3.5k citations indexed

About

Tong Chen is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Tong Chen has authored 158 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Artificial Intelligence, 63 papers in Information Systems and 31 papers in Computer Networks and Communications. Recurrent topics in Tong Chen's work include Recommender Systems and Techniques (56 papers), Advanced Graph Neural Networks (39 papers) and Topic Modeling (26 papers). Tong Chen is often cited by papers focused on Recommender Systems and Techniques (56 papers), Advanced Graph Neural Networks (39 papers) and Topic Modeling (26 papers). Tong Chen collaborates with scholars based in China, Australia and United States. Tong Chen's co-authors include Hongzhi Yin, Quoc Viet Hung Nguyen, Lizhen Cui, Zi Huang, Junliang Yu, Xin Xia, Hongxu Chen, Lei Guo, Xiangliang Zhang and Xue Li and has published in prestigious journals such as Environmental Science & Technology, Journal of Experimental Botany and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Tong Chen

130 papers receiving 3.4k citations

Hit Papers

Are Graph Augmentations Necessary? 2020 2026 2022 2024 2022 2020 2023 2023 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Are Graph Augmentations Necessary?
    2022 298 citations Junliang Yu, Hongzhi Yin et al. profile →
  2. Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation
    2020 234 citations Tong Chen, Quoc Viet Hung Nguyen et al. profile →
  3. Self-Supervised Learning for Recommender Systems: A Survey
    2023 197 citations Junliang Yu, Hongzhi Yin et al. IEEE Transactions on Knowledge and Data Engineering profile →
  4. XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation
    2023 154 citations Junliang Yu, Tong Chen et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tong Chen China 33 2.1k 1.9k 530 527 448 158 3.5k
Chao Huang China 34 2.8k 1.3× 2.0k 1.1× 684 1.3× 335 0.6× 447 1.0× 122 4.1k
Wei Koong Chai United Kingdom 21 1.2k 0.6× 1.6k 0.8× 736 1.4× 1.6k 3.0× 217 0.5× 76 3.8k
Yao Ma United States 19 2.3k 1.1× 1.1k 0.6× 612 1.2× 351 0.7× 270 0.6× 76 3.4k
Shanika Karunasekera Australia 26 1.4k 0.7× 952 0.5× 480 0.9× 1.5k 2.8× 302 0.7× 158 3.3k
Levent Koç Türkiye 5 1.3k 0.6× 1.5k 0.8× 611 1.2× 473 0.9× 121 0.3× 6 2.3k
Glen Anderson United States 5 1.1k 0.5× 1.8k 0.9× 625 1.2× 871 1.7× 121 0.3× 5 2.7k
Min Gao China 26 1.1k 0.5× 1.2k 0.6× 392 0.7× 383 0.7× 115 0.3× 190 2.5k
Heng-Tze Cheng United States 11 1.3k 0.6× 1.5k 0.8× 814 1.5× 333 0.6× 173 0.4× 19 2.4k
Yuyu Yin China 27 817 0.4× 1.1k 0.6× 434 0.8× 1.1k 2.0× 185 0.4× 117 2.5k
Yunjun Gao China 30 1.2k 0.6× 579 0.3× 746 1.4× 886 1.7× 305 0.7× 261 3.3k

Countries citing papers authored by Tong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Tong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tong Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Tong Chen. A scholar is included among the top collaborators of Tong Chen 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 Tong Chen. Tong Chen 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.
2.
3.
Yu, Junliang, et al.. (2025). BiasNavi: LLM-Empowered Data Bias Management. 2939–2942.
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Chen, Tong, Cheng‐Wei Kao, Lei Wang, et al.. (2024). Modulated t orbitals of spinel oxides for enhanced catalytic conversion of polysulfides in Li–S batteries. Materials Today Chemistry. 43. 102490–102490. 2 indexed citations
6.
Chen, Tong, et al.. (2024). Lightweight Embeddings for Graph Collaborative Filtering. 1296–1306. 4 indexed citations
7.
Chen, Tong, et al.. (2024). Budgeted Embedding Table For Recommender Systems. 557–566. 3 indexed citations
8.
Chen, Tong, et al.. (2024). FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services. ACM Transactions on Information Systems. 43(6). 1–24. 5 indexed citations
9.
Xu, Guandong, et al.. (2024). Challenging Low Homophily in Social Recommendation. 3476–3484. 12 indexed citations
10.
Chen, Tong, et al.. (2024). Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion. ACM Transactions on Information Systems. 42(6). 1–26. 6 indexed citations
11.
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Chen, Tong, et al.. (2023). Spatial-temporal meta-path guided explainable crime prediction. World Wide Web. 26(4). 2237–2263. 6 indexed citations
13.
Chen, Tong, et al.. (2023). Continuous Input Embedding Size Search For Recommender Systems. 708–717. 9 indexed citations
14.
Wen, H.C., Tong Chen, Li Kheng Chai, et al.. (2023). Variational Counterfactual Prediction Under Runtime Domain Corruption. IEEE Transactions on Knowledge and Data Engineering. 36(5). 2271–2284. 1 indexed citations
15.
Chen, Qiaomin, Bangyou Zheng, Tong Chen, & Scott Chapman. (2022). Integrating a crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning. Journal of Experimental Botany. 73(19). 6558–6574. 13 indexed citations
16.
Imran, Mubashir, Hongzhi Yin, Tong Chen, Zi Huang, & Kai Zheng. (2022). DeHIN: A Decentralized Framework for Embedding Large-Scale Heterogeneous Information Networks. IEEE Transactions on Knowledge and Data Engineering. 35(4). 3645–3657. 4 indexed citations
17.
Guo, Lei, Hongzhi Yin, Tong Chen, Xiangliang Zhang, & Kai Zheng. (2021). Hierarchical Hyperedge Embedding-Based Representation Learning for Group Recommendation. ACM Transactions on Information Systems. 40(1). 1–27. 63 indexed citations
18.
Chen, Tong, Hongzhi Yin, Xiangliang Zhang, et al.. (2021). Quaternion Factorization Machines: A Lightweight Solution to Intricate Feature Interaction Modeling. IEEE Transactions on Neural Networks and Learning Systems. 34(8). 4345–4358. 11 indexed citations
19.
Chen, Hongxu, Hongzhi Yin, Tong Chen, et al.. (2020). Social Boosted Recommendation With Folded Bipartite Network Embedding. IEEE Transactions on Knowledge and Data Engineering. 34(2). 914–926. 45 indexed citations
20.
Chen, Hongxu, Hongzhi Yin, Tong Chen, et al.. (2019). Exploiting Centrality Information with Graph Convolutions for Network Representation Learning. Griffith Research Online (Griffith University, Queensland, Australia). 590–601. 52 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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