Xiaozhou Ye

1.5k total citations · 2 hit papers
23 papers, 939 citations indexed

About

Xiaozhou Ye is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Xiaozhou Ye has authored 23 papers receiving a total of 939 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 4 papers in Electrical and Electronic Engineering and 3 papers in Computer Networks and Communications. Recurrent topics in Xiaozhou Ye's work include Topic Modeling (5 papers), Privacy-Preserving Technologies in Data (5 papers) and Natural Language Processing Techniques (4 papers). Xiaozhou Ye is often cited by papers focused on Topic Modeling (5 papers), Privacy-Preserving Technologies in Data (5 papers) and Natural Language Processing Techniques (4 papers). Xiaozhou Ye collaborates with scholars based in China, Hong Kong and New Zealand. Xiaozhou Ye's co-authors include Ming Zhu, Wei Wang, Yiqiang Sheng, Xuewen Zeng, Ye Ouyang, Ya-Qin Zhang, Yan Kang, Qiang Yang, Yang Liu and Yuanqin He and has published in prestigious journals such as PLoS ONE, Scientific Reports and Personality and Individual Differences.

In The Last Decade

Xiaozhou Ye

19 papers receiving 903 citations

Hit Papers

Malware traffic classification using convolutional neural... 2017 2026 2020 2023 2017 2024 200 400 600

Peers

Xiaozhou Ye
Comparison fields: 5 of 83
  • Artificial Intelligence 703
  • Computer Networks and Communications 627
  • Signal Processing 307
  • Information Systems 97
  • Computer Vision and Pattern Recognition 75
Replace Riccardo Spolaor with:
Riccardo Spolaor China
Chunhua Wu China
Anupam Das United States
Cheng Xu Hong Kong
Eslam Amer Egypt
Balachandra Muniyal India
Kuan‐Ta Chen Taiwan
Jorge Blasco Spain
Markus Dürmuth Germany
Riccardo Spolaor China View profile →
Citations per field, relative to Xiaozhou Ye
Xiaozhou Ye · 1×
Citations per year, relative to Xiaozhou Ye
Xiaozhou Ye · 1×

Countries citing papers authored by Xiaozhou Ye

Since Specialization
Citations

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

Fields of papers citing papers by Xiaozhou Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaozhou Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaozhou Ye. A scholar is included among the top collaborators of Xiaozhou Ye 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 Xiaozhou Ye. Xiaozhou Ye 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 1
3 3
4 2
5 0
6 0
7 19
8 0
9 1
10 3
11 11
12 1
13 2
14 9
15 6
16 2
17 6
18 55
19
Malware traffic classification using convolutional neural network for representation learning breakdown →
645
20 27

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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