Dugang Liu

536 total citations
28 papers, 278 citations indexed

About

Dugang Liu is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Dugang Liu has authored 28 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Information Systems, 19 papers in Artificial Intelligence and 14 papers in Management Science and Operations Research. Recurrent topics in Dugang Liu's work include Recommender Systems and Techniques (22 papers), Advanced Bandit Algorithms Research (13 papers) and Advanced Graph Neural Networks (9 papers). Dugang Liu is often cited by papers focused on Recommender Systems and Techniques (22 papers), Advanced Bandit Algorithms Research (13 papers) and Advanced Graph Neural Networks (9 papers). Dugang Liu collaborates with scholars based in China, Canada and Hong Kong. Dugang Liu's co-authors include Xiuqiang He, Weike Pan, Pengxiang Cheng, Zhenhua Dong, Zhong Ming, Zhong Ming, Hong Zhu, Chen Lin, Hanghang Tong and Yanghua Xiao and has published in prestigious journals such as IEEE Access, Artificial Intelligence and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Dugang Liu

20 papers receiving 271 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dugang Liu China 9 199 177 122 47 23 28 278
Tianxin Wei United States 5 247 1.2× 218 1.2× 107 0.9× 42 0.9× 15 0.7× 8 307
Flavian Vasile United States 8 198 1.0× 192 1.1× 83 0.7× 57 1.2× 28 1.2× 20 290
Changsung Kang United States 9 125 0.6× 170 1.0× 26 0.2× 45 1.0× 12 0.5× 15 235
Aghiles Salah Singapore 10 210 1.1× 181 1.0× 42 0.3× 107 2.3× 27 1.2× 14 305
Biao Li China 8 161 0.8× 130 0.7× 75 0.6× 56 1.2× 7 0.3× 13 220
João Vinagre Portugal 11 179 0.9× 139 0.8× 67 0.5× 57 1.2× 13 0.6× 24 261
Rocío Cañamares Spain 7 161 0.8× 83 0.5× 117 1.0× 25 0.5× 15 0.7× 9 182
Marcel Genzmehr Germany 6 199 1.0× 136 0.8× 39 0.3× 48 1.0× 9 0.4× 7 252
Xiaokun Zhang China 9 155 0.8× 145 0.8× 38 0.3× 41 0.9× 9 0.4× 22 215

Countries citing papers authored by Dugang Liu

Since Specialization
Citations

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

Fields of papers citing papers by Dugang Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dugang Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Dugang Liu. A scholar is included among the top collaborators of Dugang Liu 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 Dugang Liu. Dugang Liu 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
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Liu, Dugang, et al.. (2024). MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems. 434–442. 10 indexed citations
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Wen, Cheng, Zhiwu Xu, Dugang Liu, et al.. (2024). Automatically Inspecting Thousands of Static Bug Warnings with Large Language Model: How Far Are We?. ACM Transactions on Knowledge Discovery from Data. 18(7). 1–34. 14 indexed citations
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Liu, Dugang, et al.. (2023). Prior-Guided Accuracy-Bias Tradeoff Learning for CTR Prediction in Multimedia Recommendation. 995–1003. 1 indexed citations
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Liu, Dugang, et al.. (2023). Optimizing Feature Set for Click-Through Rate Prediction. 3386–3395. 15 indexed citations
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Liu, Dugang, Pengxiang Cheng, Hong Zhu, et al.. (2023). DIWIFT: Discovering Instance-wise Influential Features for Tabular Data. 1673–1682. 5 indexed citations
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Liu, Dugang, et al.. (2023). Explicit Feature Interaction-aware Uplift Network for Online Marketing. 4507–4515. 2 indexed citations
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Liu, Dugang, Pengxiang Cheng, Zhenhua Dong, et al.. (2023). Bounding System-Induced Biases in Recommender Systems with a Randomized Dataset. ACM Transactions on Information Systems. 41(4). 1–26. 6 indexed citations
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Liu, Dugang, et al.. (2023). Pairwise Intent Graph Embedding Learning for Context-Aware Recommendation. 588–598. 1 indexed citations
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He, Bowei, Minglin Ma, Jiakai Tang, et al.. (2023). Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization. 2 indexed citations
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Liu, Dugang, Pengxiang Cheng, Hong Zhu, et al.. (2022). Debiased Representation Learning in Recommendation via Information Bottleneck. 1(1). 1–27. 11 indexed citations
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Liu, Dugang, Pengxiang Cheng, Zhenhua Dong, et al.. (2022). KDCRec: Knowledge Distillation for Counterfactual Recommendation Via Uniform Data. IEEE Transactions on Knowledge and Data Engineering. 1–14. 11 indexed citations
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Liu, Dugang, Jie Huang, & Chen Lin. (2018). Recommendation With Social Roles. IEEE Access. 6. 36420–36427. 7 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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