Yonghong Yu

1.2k total citations
49 papers, 776 citations indexed

About

Yonghong Yu is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yonghong Yu has authored 49 papers receiving a total of 776 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 26 papers in Information Systems and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yonghong Yu's work include Recommender Systems and Techniques (25 papers), Advanced Graph Neural Networks (17 papers) and Expert finding and Q&A systems (6 papers). Yonghong Yu is often cited by papers focused on Recommender Systems and Techniques (25 papers), Advanced Graph Neural Networks (17 papers) and Expert finding and Q&A systems (6 papers). Yonghong Yu collaborates with scholars based in China, United Kingdom and Australia. Yonghong Yu's co-authors include Li Zhang, Chee Peng Lim, Rong Gao, Xingguo Chen, Han Liu, Hailun Xie, Yang Gao, Can Wang, Chengyu Liu and Ben Fielding and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Sensors.

In The Last Decade

Yonghong Yu

43 papers receiving 751 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yonghong Yu China 16 370 263 216 103 72 49 776
Junyang Chen China 16 423 1.1× 181 0.7× 290 1.3× 42 0.4× 67 0.9× 74 900
Shunzhi Zhu China 15 244 0.7× 83 0.3× 250 1.2× 92 0.9× 128 1.8× 94 810
Xin Dong United States 19 583 1.6× 296 1.1× 424 2.0× 28 0.3× 25 0.3× 49 988
Faliang Huang China 13 396 1.1× 133 0.5× 152 0.7× 37 0.4× 19 0.3× 50 702
Donglin Wang China 11 361 1.0× 90 0.3× 153 0.7× 84 0.8× 37 0.5× 43 601
Yingyuan Xiao China 12 194 0.5× 260 1.0× 137 0.6× 77 0.7× 92 1.3× 101 568
Huahu Xu China 14 282 0.8× 268 1.0× 149 0.7× 58 0.6× 20 0.3× 59 790

Countries citing papers authored by Yonghong Yu

Since Specialization
Citations

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

Fields of papers citing papers by Yonghong Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yonghong Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Yonghong Yu. A scholar is included among the top collaborators of Yonghong Yu 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 Yonghong Yu. Yonghong Yu 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.
Yu, Yonghong, et al.. (2025). Wasserstein distance-based graph contrastive learning for recommendation. Expert Systems with Applications. 297. 129427–129427.
2.
3.
Yu, Yonghong, et al.. (2025). Contrastive Translation With Dynamical Temperature for Sequential Recommendation. IEEE Transactions on Systems Man and Cybernetics Systems. 55(6). 4273–4285. 1 indexed citations
4.
Yu, Yonghong, et al.. (2024). Contrastive Learning-Based Personalized Tag Recommendation. Sensors. 24(18). 6061–6061. 1 indexed citations
5.
Zhang, Li, Dezong Zhao, Chee Peng Lim, et al.. (2024). Video Deepfake classification using particle swarm optimization-based evolving ensemble models. Knowledge-Based Systems. 289. 111461–111461. 13 indexed citations
6.
Yu, Yonghong, et al.. (2024). Hyperbolic Translation-Based Sequential Recommendation. IEEE Transactions on Computational Social Systems. 11(6). 7467–7483. 4 indexed citations
7.
Gao, Rong, Jiming Wang, Yonghong Yu, Jia Wu, & Li Zhang. (2024). Enhanced graph diffusion learning with dynamic transformer for anomaly detection in multivariate time series. Neurocomputing. 619. 129168–129168. 5 indexed citations
8.
Gao, Rong, et al.. (2023). Self-supervised Dual Hypergraph learning with Intent Disentanglement for session-based recommendation. Knowledge-Based Systems. 270. 110528–110528. 23 indexed citations
9.
Zhang, Li, et al.. (2023). A Graph Neural Networks-Based Learning Framework With Hyperbolic Embedding for Personalized Tag Recommendation. IEEE Access. 12. 339–350. 4 indexed citations
10.
Zhang, Li, Haoqian Huang, Houshyar Asadi, et al.. (2023). Neural Inference Search for Multiloss Segmentation Models. IEEE Transactions on Neural Networks and Learning Systems. 35(11). 15113–15127. 9 indexed citations
11.
Song, Peng, Yonghong Yu, & Yang Zhang. (2023). TTH-Net: Two-Stage Transformer–CNN Hybrid Network for Leaf Vein Segmentation. Applied Sciences. 13(19). 11019–11019. 1 indexed citations
12.
Gao, Rong, Yonghong Yu, Jia Wu, et al.. (2023). Contrastive graph learning long and short-term interests for POI recommendation. Expert Systems with Applications. 238. 121931–121931. 25 indexed citations
13.
Zhang, Li, et al.. (2022). A Deep Ensemble Neural Network with Attention Mechanisms for Lung Abnormality Classification Using Audio Inputs. Sensors. 22(15). 5566–5566. 19 indexed citations
14.
Yu, Yonghong, et al.. (2022). A Graph-Neural-Network-Based Social Network Recommendation Algorithm Using High-Order Neighbor Information. Sensors. 22(19). 7122–7122. 17 indexed citations
15.
Yu, Yonghong, et al.. (2020). Neural Graph for Personalized Tag Recommendation. IEEE Intelligent Systems. 37(1). 51–59. 15 indexed citations
16.
Gao, Rong, et al.. (2020). HHA: An Attentive Prediction Model for Academic Abnormality. IEEE Access. 8. 124755–124766. 4 indexed citations
17.
Zhang, Li, et al.. (2019). Evolving Ensemble Models for Image Segmentation Using Enhanced Particle Swarm Optimization. IEEE Access. 7. 34004–34019. 98 indexed citations
18.
Wang, Qiang, et al.. (2019). Network Representation Learning Enhanced Recommendation Algorithm. IEEE Access. 7. 61388–61399. 5 indexed citations
19.
Yu, Yonghong & Xingguo Chen. (2015). A Survey of Point-of-Interest Recommendation in Location-Based Social Networks. National Conference on Artificial Intelligence. 57 indexed citations
20.
Yu, Yonghong. (2006). Heterogeneous data sources integration based on XML middleware.

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Junyang Chen Breakdown of academic impact, for papers by Shunzhi Zhu Breakdown of academic impact, for papers by Xin Dong Breakdown of academic impact, for papers by Faliang Huang Breakdown of academic impact, for papers by Donglin Wang Breakdown of academic impact, for papers by Yingyuan Xiao Breakdown of academic impact, for papers by Huahu Xu
Rankless by CCL
2026