Peipei Li

4.5k citations
177 papers · 3.1k · h-index 30

Impact in

Papers in

    • Text and Document Classification Technologies 37
    • Data Stream Mining Techniques 25
    • Topic Modeling 16
    • Domain Adaptation and Few-Shot Learning 14
    • Machine Learning and Data Classification 12
    • Spam and Phishing Detection 14
    • Web Data Mining and Analysis 10
    • Recommender Systems and Techniques 10

Peipei Li

157 papers receiving 3.0k citations

Peers

Peipei Li
Comparison fields: 5 of 173
  • Artificial Intelligence 1.5k
  • Computer Vision and Pattern Recognition 647
  • Information Systems 488
  • Signal Processing 215
  • Clinical Psychology 351
Replace Zhenyu Chen with:
Zhenyu Chen China
Jin Liu China
Can Wang China
Ambuj Tewari United States
David E. Smith United States
Yuqing Zhang China
Peter Eklund Australia
Shaoxiong Ji Finland
Jingyuan Wang China
Tutut Herawan Malaysia
Peipei Li relative to Zhenyu Chen China Zhenyu Chen's profile →
Citations per field
00.5×3.4×
Zhenyu Chen · 1×
Citations per year

Countries citing papers authored by Peipei Li

Since Specialization
Citations

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

Fields of papers citing papers by Peipei Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 177 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012218
2 2014178
3 2017137
4 2020118
5 202189
6 202086
7 201883
8 201680
9 202178
10 201877
11 201763
12 201259
13 202157
14 201955
15 202251
16 202149
17 200945
18 202044
19 201543
20 202243

About Peipei Li

Peipei Li is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Molecular Biology and Computer Networks and Communications, having authored 177 papers that have together received 3.1k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (37 papers), Data Stream Mining Techniques (25 papers), Topic Modeling (16 papers), Domain Adaptation and Few-Shot Learning (14 papers), Spam and Phishing Detection (14 papers), Machine Learning and Data Classification (12 papers), Web Data Mining and Analysis (10 papers) and Recommender Systems and Techniques (10 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Computer Vision and Pattern Recognition (647 citations), Information Systems (488 citations), Signal Processing (215 citations) and Clinical Psychology (351 citations). Peipei Li has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Xuegang Hu, Xindong Wu, Peng Zhou, Yuhong Zhang, Kui Yu, Youyu Zhang, Meng Wang, Canyi Lu, Shuicheng Yan and Huiting Liu. Their work appears in journals such as Knowledge-Based Systems, Neurocomputing, Pattern Recognition, Information Sciences and Expert Systems with Applications.

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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