Pengfei Wang

2.6k total citations · 1 hit paper
92 papers, 1.5k citations indexed

About

Pengfei Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Pengfei Wang has authored 92 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 31 papers in Computer Vision and Pattern Recognition and 30 papers in Information Systems. Recurrent topics in Pengfei Wang's work include Recommender Systems and Techniques (26 papers), Topic Modeling (18 papers) and Advanced Graph Neural Networks (15 papers). Pengfei Wang is often cited by papers focused on Recommender Systems and Techniques (26 papers), Topic Modeling (18 papers) and Advanced Graph Neural Networks (15 papers). Pengfei Wang collaborates with scholars based in China, United States and Japan. Pengfei Wang's co-authors include Jiafeng Guo, Yanyan Lan, Jun Xu, Shengxian Wan, Xueqi Cheng, Chenliang Li, Wayne Xin Zhao, Shaozhang Niu, Ji-Rong Wen and Fan Yu and has published in prestigious journals such as PLoS ONE, Research Policy and Chemical Physics Letters.

In The Last Decade

Pengfei Wang

80 papers receiving 1.5k citations

Hit Papers

RecBole: Towards a Unified, Comprehensive and Efficient F... 2021 2026 2022 2024 2021 50 100 150 200

Peers

Pengfei Wang
Comparison fields: 5 of 111
  • Information Systems 876
  • Artificial Intelligence 803
  • Computer Vision and Pattern Recognition 405
  • Management Science and Operations Research 232
  • Transportation 102
Replace Shuaiqiang Wang with:
Shuaiqiang Wang China
Zheng Qin China
Erik Mannens Belgium
Shou-De Lin Taiwan
Xu Chen China
Flora Amato Italy
Norafida Ithnin Malaysia
Sadok Ben Yahia Tunisia
Asad Masood Khattak United Arab Emirates
Shuaiqiang Wang China View profile →
Citations per field, relative to Pengfei Wang
Pengfei Wang · 1×
Citations per year, relative to Pengfei Wang
Pengfei Wang · 1×

Countries citing papers authored by Pengfei Wang

Since Specialization
Citations

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

Fields of papers citing papers by Pengfei Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengfei Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Pengfei Wang. A scholar is included among the top collaborators of Pengfei Wang 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 Pengfei Wang. Pengfei Wang 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
# Work Indexed citations
1 1
2 0
3 1
4 0
5 0
6 17
7 1
8 7
9 0
10 2
11 1
12 3
13 21
14 1
15 40
16 2
17 0
18
Next Basket Recommendation with Neural Networks.
9
19
The Extension of Double Integral Mean Value Theorem
0
20 1

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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