Xiaoyan Cai

1.8k total citations
73 papers, 1.1k citations indexed

About

Xiaoyan Cai is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Xiaoyan Cai has authored 73 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Artificial Intelligence, 23 papers in Information Systems and 9 papers in Computer Networks and Communications. Recurrent topics in Xiaoyan Cai's work include Topic Modeling (43 papers), Natural Language Processing Techniques (22 papers) and Recommender Systems and Techniques (19 papers). Xiaoyan Cai is often cited by papers focused on Topic Modeling (43 papers), Natural Language Processing Techniques (22 papers) and Recommender Systems and Techniques (19 papers). Xiaoyan Cai collaborates with scholars based in China, Australia and Hong Kong. Xiaoyan Cai's co-authors include Libin Yang, Wenjie Li, Junwei Han, Lantian Guo, Shirui Pan, Tao Dai, Dejun Mu, Dejun Mu, Yu Zheng and Renxian Zhang and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Xiaoyan Cai

70 papers receiving 1.1k citations

Peers

Xiaoyan Cai
Comparison fields: 5 of 92
  • Artificial Intelligence 886
  • Information Systems 440
  • Computer Vision and Pattern Recognition 129
  • Statistical and Nonlinear Physics 110
  • Computer Networks and Communications 86
Replace Libin Yang with:
Libin Yang China
Xiaozhi Wang China
Shiwan Zhao China
Georgiana Ifrim Ireland
Enrique Amigó Spain
Wenhu Chen United States
Weiwen Liu China
Shumin Deng China
Yukuo Cen China
Libin Yang China View profile →
Citations per field, relative to Xiaoyan Cai
Xiaoyan Cai · 1×
Citations per year, relative to Xiaoyan Cai
Xiaoyan Cai · 1×

Countries citing papers authored by Xiaoyan Cai

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoyan Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoyan Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoyan Cai. A scholar is included among the top collaborators of Xiaoyan Cai 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 Xiaoyan Cai. Xiaoyan Cai 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 8
2 0
3 9
4 1
5 15
6 28
7 6
8 2
9 0
10 11
11 7
12 11
13 4
14 10
15 53
16 15
17 39
18 34
19 28
20
An Anomaly Detection Scheme for Wireless Sensor Networks Based on Kernel Clustering
1

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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