Dunlu Peng

737 citations
55 papers · 451 · h-index 14

Impact in

Papers in

    • Topic Modeling 11
    • Advanced Graph Neural Networks 8
    • Text and Document Classification Technologies 7
    • Natural Language Processing Techniques 6
    • Recommender Systems and Techniques 12
    • Service-Oriented Architecture and Web Services 8
    • Web Data Mining and Analysis 4

Dunlu Peng

47 papers receiving 440 citations

Peers

Dunlu Peng
Comparison fields: 5 of 94
  • Artificial Intelligence 210
  • Computer Vision and Pattern Recognition 115
  • Information Systems 112
  • Building and Construction 36
  • Signal Processing 23
Replace Ruiqin Wang with:
Ruiqin Wang China
Zhongyi Zhai China
Fangyu Wu China
Eugenio Zimeo Italy
Yinan Shao China
Liuyi Yao United States
Mohammed Elbes Jordan
Yiqi Wang China
Dunlu Peng relative to Ruiqin Wang China Ruiqin Wang's profile →
Citations per field
00.5×5.5×
Ruiqin Wang · 1×
Citations per year

Countries citing papers authored by Dunlu Peng

Since Specialization
Citations

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

Fields of papers citing papers by Dunlu Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202144
2 201533
3 201928
4 202026
5 202322
6 201821
7 202019
8 201919
9 202118
10 201917
11 202016
12 202415
13 202015
14 202214
15 200913
16 202113
17 202210
18 20219
19 20249
20 20208

About Dunlu Peng

Dunlu Peng is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 55 papers that have together received 451 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (12 papers), Topic Modeling (11 papers), Service-Oriented Architecture and Web Services (8 papers), Advanced Graph Neural Networks (8 papers), Text and Document Classification Technologies (7 papers), Natural Language Processing Techniques (6 papers), Web Data Mining and Analysis (4 papers) and Traffic Prediction and Management Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (210 citations), Computer Vision and Pattern Recognition (115 citations), Information Systems (112 citations), Building and Construction (36 citations) and Signal Processing (23 citations). Dunlu Peng has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Cong Liu, Cong Liu, Wuchen Yang, Jianping Lu, Yongsheng Zhang, Lei Wang, Wenjia Peng, Chunxue Wu, Zhan Su and Jun Ai. Their work appears in journals such as Expert Systems with Applications, IEEE Access, Applied Soft Computing, Engineering Applications of Artificial Intelligence and Information Systems Frontiers.

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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