Wenge Rong

2.1k total citations
102 papers, 1.1k citations indexed

About

Wenge Rong is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Wenge Rong has authored 102 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Artificial Intelligence, 41 papers in Information Systems and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Wenge Rong's work include Topic Modeling (45 papers), Natural Language Processing Techniques (28 papers) and Recommender Systems and Techniques (20 papers). Wenge Rong is often cited by papers focused on Topic Modeling (45 papers), Natural Language Processing Techniques (28 papers) and Recommender Systems and Techniques (20 papers). Wenge Rong collaborates with scholars based in China, United Kingdom and Australia. Wenge Rong's co-authors include Zhang Xiong, Yuanxin Ouyang, Kecheng Liu, Yuanxin Ouyang, Hui Chen, Baolin Peng, Chuantao Yin, Yikang Shen, Yue Qu and Min Gao and has published in prestigious journals such as IEEE Access, BMC Bioinformatics and Neurocomputing.

In The Last Decade

Wenge Rong

95 papers receiving 1.0k citations

Peers

Wenge Rong
Nicholas Gibbins United Kingdom
Nicola Ferro Italy
George Lepouras Greece
Joeran Beel Germany
Fabien Gandon France
Fabio Vitali Italy
Vincent Wade Ireland
Bernhard Haslhofer Austria
Ibrahim Almarashdeh Saudi Arabia
Julia Stoyanovich United States
Nicholas Gibbins United Kingdom
Wenge Rong
Citations per year, relative to Wenge Rong Wenge Rong (= 1×) peers Nicholas Gibbins

Countries citing papers authored by Wenge Rong

Since Specialization
Citations

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

Fields of papers citing papers by Wenge Rong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wenge Rong

This figure shows the co-authorship network connecting the top 25 collaborators of Wenge Rong. A scholar is included among the top collaborators of Wenge Rong 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 Wenge Rong. Wenge Rong 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.
Yin, Chuantao, et al.. (2024). TOCOL: improving contextual representation of pre-trained language models via token-level contrastive learning. Machine Learning. 113(7). 3999–4012. 1 indexed citations
2.
Ouyang, Yuanxin, et al.. (2024). Wasserstein Dependent Graph Attention Network for Collaborative Filtering With Uncertainty. IEEE Transactions on Computational Social Systems. 12(1). 152–162. 1 indexed citations
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Zhang, Xiong, Zhuang Liu, Zhuofan Chen, et al.. (2024). A Review of Data Mining in Personalized Education: Current Trends and Future Prospects. arXiv (Cornell University). 2 indexed citations
5.
Zhang, Xiong, Zhuang Liu, Zhuofan Chen, et al.. (2024). A Review of Data Mining in Personalized Education: Current Trends and Future Prospects. 1(1). 26–50. 4 indexed citations
6.
Li, Hao, et al.. (2024). Addressing Over-Squashing in GNNs with Graph Rewiring and Ordered Neurons. 1–8. 2 indexed citations
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Rong, Wenge, et al.. (2023). Multisource Soft Labeling and Hard Negative Sampling for Retrieval Distractor Ranking. IEEE Transactions on Learning Technologies. 17. 664–676. 1 indexed citations
9.
Rong, Wenge, et al.. (2023). Factors that impacted mobile-payment adoption in China during the COVID-19 pandemic. Heliyon. 9(5). e16197–e16197. 15 indexed citations
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Huang, Shaofei, Han Li, Yuqing Wang, et al.. (2023). Discovering Sounding Objects by Audio Queries for Audio Visual Segmentation. 875–883. 8 indexed citations
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Rong, Wenge, et al.. (2022). Token Relation Aware Chinese Named Entity Recognition. ACM Transactions on Asian and Low-Resource Language Information Processing. 22(1). 1–21. 4 indexed citations
15.
Rong, Wenge, et al.. (2021). External features enriched model for biomedical question answering. BMC Bioinformatics. 22(1). 272–272. 18 indexed citations
16.
Li, Wentao, et al.. (2021). Manipulating Black-Box Networks for Centrality Promotion. 73–84. 3 indexed citations
17.
Ouyang, Yuanxin, et al.. (2019). Similarity Based Auxiliary Classifier for Named Entity Recognition. 1140–1149. 5 indexed citations
18.
Qiao, Lei, et al.. (2019). Automated Constmction of Course Knowledge Graph Based on China MOOC Platform. 1–7. 1 indexed citations
19.
Rong, Wenge, et al.. (2017). Visual and Audio Aware Bi-Modal Video Emotion Recognition.. Cognitive Science. 2 indexed citations
20.
Zhang, Xiang, Wenge Rong, Jingshuang Liu, Chuan Tian, & Zhang Xiong. (2017). Convolution neural network based syntactic and semantic aware paraphrase identification. 2158–2163. 8 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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