Kaigui Wu

420 citations
37 papers · 269 · h-index 7

Impact in

Papers in

Kaigui Wu

31 papers receiving 256 citations

Peers

Kaigui Wu
Comparison fields: 5 of 60
  • Software 27
  • Computer Networks and Communications 70
  • Safety, Risk, Reliability and Quality 26
  • Biomedical Engineering 123
  • Information Systems 52
Replace Shuyu Guo with:
Shuyu Guo China
M. Rodgers United States
Lei Shang China
M. Favalli Italy
Luyao Ren China
Fathollah Bistouni Iran
Yunzhi Jiang China
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Yongbo Li China
Kaigui Wu relative to Shuyu Guo China Shuyu Guo's profile →
Citations per field
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Citations per year

Countries citing papers authored by Kaigui Wu

Since Specialization
Citations

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

Fields of papers citing papers by Kaigui Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012128
2 201223
3 200517
4 202013
5 20118
6 20127
7 20116
8 20105
9 20104
10 20084
11 20024
12 20214
13 20044
14 20084
15 20114
16 20104
17 20094
18 20034
19 20123
20
Methodology for Entities Matching Based on Attribute Information Entropy
20052

About Kaigui Wu

Kaigui Wu is a scholar working on Computer Networks and Communications, Information Systems, Artificial Intelligence, Software and Computer Vision and Pattern Recognition, having authored 37 papers that have together received 269 indexed citations. Recurring topics across this work include Cryptography and Data Security (7 papers), Service-Oriented Architecture and Web Services (7 papers), Software Reliability and Analysis Research (6 papers), Software System Performance and Reliability (5 papers), Advanced Authentication Protocols Security (5 papers), Data Management and Algorithms (4 papers), Reliability and Maintenance Optimization (4 papers) and Cloud Data Security Solutions (4 papers). The work is most often cited by research in Software (27 citations), Computer Networks and Communications (70 citations), Safety, Risk, Reliability and Quality (26 citations), Biomedical Engineering (123 citations) and Information Systems (52 citations). Kaigui Wu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Qiu Cui, Caifeng Bi, Yu Tang, Jitian Liu, Jie Xu, Zhongfu Wu, Junhao Wen, Zhuo Jiang, Pan He and Yong Feng. Their work appears in journals such as IEEE Access, INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences, Computers & Industrial Engineering, Future Generation Computer Systems and Carbohydrate Research.

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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