Yu Lei

1.1k total citations · 1 hit paper
15 papers, 481 citations indexed

About

Yu Lei is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Yu Lei has authored 15 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 9 papers in Information Systems and 3 papers in Computer Networks and Communications. Recurrent topics in Yu Lei's work include Recommender Systems and Techniques (7 papers), Topic Modeling (6 papers) and Advanced Graph Neural Networks (4 papers). Yu Lei is often cited by papers focused on Recommender Systems and Techniques (7 papers), Topic Modeling (6 papers) and Advanced Graph Neural Networks (4 papers). Yu Lei collaborates with scholars based in Hong Kong, China and United States. Yu Lei's co-authors include Wenjie Li, Yuxia Sun, Fangxi Zhang, Xin Dong, Yang Lu, Zhitao Wang, Hongbin Pei, Haiying Shen, Jinwei Liu and Yanxiang He and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Services Computing.

In The Last Decade

Yu Lei

13 papers receiving 456 citations

Hit Papers

align trajectories

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.

A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems

2017 184 citations Xin Dong, Yu Lei et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers

Countries citing papers authored by Yu Lei

Since Specialization

Citations

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

Fields of papers citing papers by Yu Lei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yu Lei

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Lei. A scholar is included among the top collaborators of Yu Lei 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 Yu Lei. Yu Lei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Research on Intelligent Digital Archive Management Based on Knowledge Graph 2024 ·Yu Lei, Huijun Wang, Fengjiao Xu	0
2	Reinforcement Learning based Recommendation with Graph Convolutional Q-network 2020 ·Yu Lei, Hongbin Pei, (unknown), Wenjie Li	31
3	Social Attentive Deep Q-Networks for Recommender Systems 2020 ·IEEE Transactions on Knowledge and Data Engineering ·Yu Lei, Zhitao Wang, Wenjie Li, Hongbin Pei, Quanyu Dai	15
4	Neighborhood Attention Networks With Adversarial Learning for Link Prediction 2020 ·IEEE Transactions on Neural Networks and Learning Systems ·Zhitao Wang, Yu Lei, Wenjie Li	21
5	Personalized project recommendations: using reinforcement learning 2019 ·EURASIP Journal on Wireless Communications and Networking ·(unknown), Xiangrong Tong, Yu Lei, Yingjie Wang	5
6	Social Attentive Deep Q-network for Recommendation 2019 ·Yu Lei, Zhitao Wang, Wenjie Li, Hongbin Pei	21
7	IPSO: A Scaling Model for Data-Intensive Applications 2019 ·Zhongwei Li, (unknown), Minh Nguyen, Hao Che, Yu Lei, Hong Jiang	0
8	Interactive Recommendation with User-Specific Deep Reinforcement Learning 2019 ·ACM Transactions on Knowledge Discovery from Data ·Yu Lei, Wenjie Li	35
9	Neighborhood Interaction Attention Network for Link Prediction 2019 ·Zhitao Wang, Yu Lei, Wenjie Li	4
10	Variational Recurrent Model for Session-based Recommendation 2018 ·Zhitao Wang, (unknown), Ke Zhang, Yu Lei, Wenjie Li	12
11	A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems breakdown → 2017 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Xin Dong, Yu Lei, (unknown), Yuxia Sun, (unknown), Fangxi Zhang	184
12	Alternating Pointwise-Pairwise Learning for Personalized Item Ranking 2017 ·PolyU Institutional Research Archive (Hong Kong Polytechnic University) ·Yu Lei, Wenjie Li, (unknown), Miao Zhao	14
13	Learning to Adapt Credible Knowledge in Cross-lingual Sentiment Analysis 2015 ·Qiang Chen, Wenjie Li, Yu Lei, (unknown), Yanxiang He	22
14	Question Quality Analysis and Prediction in Community Question Answering Services with Coupled Mutual Reinforcement 2015 ·IEEE Transactions on Services Computing ·Jinwei Liu, Haiying Shen, Yu Lei	37
15	Smart Hospital based on Internet of Things 2012 ·Journal of Networks ·Yu Lei, Yang Lu, (unknown)	80

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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