Yong Liu

207 papers receiving 4.5k citations

Hit Papers

How Can Recommender Systems Benefit from Large Language Models: A Survey 2024 · 53 citations
530+4+8Years since publication100200300

Peers

Yong Liu
Comparison fields: 5 of 158
  • Transportation 716
  • Information Systems 1.9k
  • Artificial Intelligence 1.7k
  • Computational Mathematics 26
  • Computer Vision and Pattern Recognition 744
Replace Aditya Grover with:
Aditya Grover United States
Ling Chen China
Cheng Yang China
Yuxiao Dong China
Jia Wu Australia
Longbing Cao Australia
Peng Cui China
Bin Cui China
Yizhou Sun United States
Lichan Hong United States
Yong Liu relative to Aditya Grover United States Aditya Grover's profile →
Citations per field
00.5×9.4×
Aditya Grover · 1×
Citations per year

Countries citing papers authored by Yong Liu

Since Specialization
Citations

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

Fields of papers citing papers by Yong Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yong Liu, 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 Yong Liu Line = papers co-authored together Yong Liu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 225 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A survey of collaborative filtering based social recommender systems
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2013342
2 2016284
3
Exploiting Geographical Neighborhood Characteristics for Location Recommendation
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2014236
4 2013191
5
Insights into PPLive: A Measurement Study of a Large-Scale P2P IPTV System
2006136
6 2006119
7 2012113
8 2012111
9 2014104
10 2019104
11
Bootstrap Latent Representations for Multi-modal Recommendation
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2023103
12 202297
13 202181
14 202067
15 201163
16 202063
17 202062
18 202061
19
Exploring the context of locations for personalized location recommendations
201661
20 201659

About Yong Liu

Yong Liu is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Computational Theory and Mathematics, having authored 225 papers that have together received 4.6k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (52 papers), Advanced Graph Neural Networks (30 papers), Topic Modeling (18 papers), Human Mobility and Location-Based Analysis (14 papers), Computational Drug Discovery Methods (12 papers), Advanced Bandit Algorithms Research (11 papers), Multimodal Machine Learning Applications (10 papers) and Bioinformatics and Genomic Networks (10 papers). The work is most often cited by research in Transportation (716 citations), Information Systems (1.9k citations), Artificial Intelligence (1.7k citations), Computational Mathematics (26 citations) and Computer Vision and Pattern Recognition (744 citations). Yong Liu has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Chunyan Miao, Xiwang Yang, Min Wu, Xiaoli Li, Aixin Sun, Harald Steck, Peilin Zhao, Yang Guo, Xin Liu and Wei Wei. Their work appears in journals such as Bioinformatics, Knowledge-Based Systems, IEEE Transactions on Knowledge and Data Engineering, IEEE Access and IEEE Transactions on Neural Networks and Learning Systems.

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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