Le Wu

6.2k citations

117 papers · 3.7k indexed · 4 hit papers · h-index 31

Impact in

Information Systems top 0.1%
- Recommender Systems and Techniques
Artificial Intelligence top 0.5%
- Advanced Graph Neural Networks
- Topic Modeling

Papers in ⓘ

Information Systems 62
- Recommender Systems and Techniques 56
Artificial Intelligence 70
- Advanced Graph Neural Networks 41
- Topic Modeling 24
- Intelligent Tutoring Systems and Adaptive Learning 9

Co-authors: Meng Wang (39 shared papers)Richang Hong (37 shared papers)Peijie Sun (13 shared papers)Kun Zhang (27 shared papers)Yanjie Fu (7 shared papers)Enhong Chen (30 shared papers)Xiting Wang (4 shared papers)Lei Chen (1 shared paper)
Journals: IEEE Transactions on Knowledge and Data Engineering (9 papers)ACM Transactions on Information Systems (5 papers)IEEE Transactions on Systems Man and Cybernetics Systems (4 papers)IEEE Transactions on Multimedia (3 papers)Science China Information Sciences (3 papers)
Partner nations: China United States Poland

In The Last Decade

Le Wu

110 papers receiving 3.6k citations

Hit Papers

align trajectories log scale

A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation 2022 · 250 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2022 IEEE Transactions on Knowledge and Data Engineering
2020 IEEE Transactions on Knowledge and Data Engineering
2020 Proceedings of the AAAI Conference on Artificial Intelligence
2019 A Neural Influence Diffusion Model for Social Recommendation

Peers

Countries citing papers authored by Le Wu

Since Specialization

Citations

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

Fields of papers citing papers by Le Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Le Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Le Wu Line = papers co-authored together Le Wu links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 117 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach Proceedings of the AAAI Conference on Artificial Intelligence ·Lei Chen, Le Wu, Richang Hong, Kun Zhang, Meng Wang Hit paper breakdown →	2020	374
2	A Neural Influence Diffusion Model for Social Recommendation Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang, Meng Wang Hit paper breakdown →	2019	365
3	A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendation IEEE Transactions on Knowledge and Data Engineering ·Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang Hit paper breakdown →	2022	250
4	DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation IEEE Transactions on Knowledge and Data Engineering ·Le Wu, Junwei Li, Peijie Sun, Richang Hong, Yong Ge, Meng Wang Hit paper breakdown →	2020	222
5	Understanding employees’ energy saving behavior from the perspective of stimulus-organism-responses Resources Conservation and Recycling ·Zhenya Tang, Merrill Warkentin, Le Wu	2018	125
6	Graph Convolutional Networks with Markov Random Field Reasoning for Social Spammer Detection Proceedings of the AAAI Conference on Artificial Intelligence ·Yongji Wu, Defu Lian, Yiheng Xu, Le Wu, Enhong Chen	2020	108
7	Modeling the Evolution of Users’ Preferences and Social Links in Social Networking Services IEEE Transactions on Knowledge and Data Engineering ·Le Wu, Yong Ge, Qi Liu, Enhong Chen, Richang Hong, Junping Du, Meng Wang	2017	94
8	Attentive Recurrent Social Recommendation Peijie Sun, Le Wu, Meng Wang	2018	87
9	A Review-aware Graph Contrastive Learning Framework for Recommendation Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval ·Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li	2022	86
10	A Reinforcement Learning Framework for Explainable Recommendation Xiting Wang, Yiru Chen, Jie Yang, Le Wu, Zhengtao Wu, Xing Xie	2018	85
11	Learning Fair Representations for Recommendation: A Graph-based Perspective Le Wu, Lei Chen, Pengyang Shao, Richang Hong, Xiting Wang, Meng Wang	2021	84
12	Collaborative Neural Social Recommendation IEEE Transactions on Systems Man and Cybernetics Systems ·Le Wu, Peijie Sun, Richang Hong, Yong Ge, Meng Wang	2018	81
13	Learning or Forgetting? A Dynamic Approach for Tracking the Knowledge Proficiency of Students ACM Transactions on Information Systems ·Zhenya Huang, Qi Liu, Yuying Chen, Le Wu, Keli Xiao, Enhong Chen, Haiping Ma, Guoping Hu	2020	73
14	Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization Yonghui Yang, Le Wu, Richang Hong, Kun Zhang, Meng Wang	2021	70
15	Joint Item Recommendation and Attribute Inference Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Yanjie Fu, Meng Wang	2020	67
16	Dual Learning for Explainable Recommendation: Towards Unifying User Preference Prediction and Review Generation Peijie Sun, Le Wu, Kun Zhang, Yanjie Fu, Richang Hong, Meng Wang	2020	60
17	Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning Proceedings of the ACM Web Conference 2022 ·Xiting Wang, Kunpeng Liu, Dongjie Wang, Le Wu, Yanjie Fu, Xing Xie	2022	58
18	Leveraging tagging for neighborhood-aware probabilistic matrix factorization Le Wu, Enhong Chen, Qi Liu, Linli Xu, Tengfei Bao, Lei Zhang	2012	55
19	Tracking Knowledge Proficiency of Students with Educational Priors Yuying Chen, Qi Liu, Zhenya Huang, Le Wu, Enhong Chen, Runze Wu, Yu Su, Guoping Hu	2017	53
20	ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation IET Computer Vision ·Xin Jin, Le Wu, Xiaodong Li, Xiaokun Zhang, Jingying Chi, Siwei Peng, Shiming Ge, Geng Zhao, Shuying Li	2018	48

About Le Wu

Le Wu is a scholar working on Information Systems, Artificial Intelligence, Computer Science Applications, Computer Vision and Pattern Recognition and Health Informatics, having authored 117 papers that have together received 3.7k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (56 papers), Advanced Graph Neural Networks (41 papers), Topic Modeling (24 papers), Multimodal Machine Learning Applications (10 papers), Intelligent Tutoring Systems and Adaptive Learning (9 papers), Advanced Image and Video Retrieval Techniques (9 papers), Caching and Content Delivery (8 papers) and Online Learning and Analytics (7 papers). The work is most often cited by research in Information Systems (2.3k citations), Artificial Intelligence (2.4k citations), Computer Vision and Pattern Recognition (757 citations), Computer Science Applications (192 citations) and Transportation (201 citations). Le Wu has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Meng Wang, Richang Hong, Peijie Sun, Kun Zhang, Yanjie Fu, Enhong Chen, Xiting Wang, Lei Chen, Xiangnan He and Qi Liu. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information Systems, IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Transactions on Multimedia and Science China Information Sciences.

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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