Dunlu Peng

708 citations
53 papers · 429 · 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
    • Sentiment Analysis and Opinion Mining 4
    • Recommender Systems and Techniques 11
    • Service-Oriented Architecture and Web Services 8

Dunlu Peng

47 papers receiving 416 citations

Peers

Dunlu Peng
Comparison fields: 5 of 93
  • Artificial Intelligence 207
  • Computer Vision and Pattern Recognition 111
  • Information Systems 109
  • Building and Construction 33
  • Signal Processing 22
Replace Ruiqin Wang with:
Ruiqin Wang China
Eleana Asimakopoulou United Kingdom
Zhongyi Zhai China
Eugenio Zimeo Italy
Mohammed Elbes Jordan
Longkun Guo China
Yinan Shao China
Fangyu Wu 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 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202139
2 201532
3 201928
4 202024
5 201821
6 202320
7 201919
8 202118
9 202017
10 201917
11 202016
12 202015
13 202214
14 202113
15 200913
16 202411
17 202210
18 20208
19 20218
20 20058

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 53 papers that have together received 429 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (11 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), Sentiment Analysis and Opinion Mining (4 papers) and Complex Network Analysis Techniques (4 papers). The work is most often cited by research in Artificial Intelligence (207 citations), Computer Vision and Pattern Recognition (111 citations), Information Systems (109 citations), Building and Construction (33 citations) and Signal Processing (22 citations). Dunlu Peng has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Cong Liu, Cong Liu, Wenjia Peng, Jianping Lu, Lei Wang, Yongsheng Zhang, Wuchen Yang, Chunxue Wu, Ming Zhou and Shuo Zhang. Their work appears in journals such as Expert Systems with Applications, IEEE Access, Applied Soft Computing, Information Systems Frontiers and Knowledge-Based 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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