Baolin Yi

984 citations
40 papers · 650 · h-index 11

Impact in

Papers in

Baolin Yi

38 papers receiving 630 citations

Peers

Baolin Yi
Comparison fields: 5 of 87
  • Computer Science Applications 110
  • Information Systems 367
  • Artificial Intelligence 301
  • Computational Mathematics 5
  • Computer Vision and Pattern Recognition 145
Replace Giuseppe Sansonetti with:
Giuseppe Sansonetti Italy
Chhavi Rana India
J. Javier Samper Spain
Abdul Rahim Ahmad Malaysia
Fernando Díez Spain
Deren Chen China
Guillermo Licea Mexico
Jiahui Chen China
Ikram Amous Tunisia
Baolin Yi relative to Giuseppe Sansonetti Italy Giuseppe Sansonetti's profile →
Citations per field
00.5×3.5×
Giuseppe Sansonetti · 1×
Citations per year

Countries citing papers authored by Baolin Yi

Since Specialization
Citations

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

Fields of papers citing papers by Baolin Yi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019164
2 2017159
3 201963
4 201640
5 202227
6 202424
7 202424
8 201022
9 202419
10 201612
11 201912
12 20068
13 20078
14 20188
15 20177
16 20176
17 20245
18 20065
19 20234
20 20254

About Baolin Yi

Baolin Yi is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Computer Science Applications and Computer Vision and Pattern Recognition, having authored 40 papers that have together received 650 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (14 papers), Online Learning and Analytics (7 papers), Advanced Graph Neural Networks (7 papers), Topic Modeling (6 papers), Educational Technology and Assessment (5 papers), Energy Efficient Wireless Sensor Networks (4 papers), Image Retrieval and Classification Techniques (4 papers) and Electrocatalysts for Energy Conversion (3 papers). The work is most often cited by research in Computer Science Applications (110 citations), Information Systems (367 citations), Artificial Intelligence (301 citations), Computational Mathematics (5 citations) and Computer Vision and Pattern Recognition (145 citations). Baolin Yi has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Xiaoxuan Shen, Zhaoli Zhang, Jiangbo Shu, Hai Liu, Sannyuya Liu, Wei Zhang, Naixue Xiong, Hai Liu, Yao Zhao and Hangzhou Zhang. Their work appears in journals such as Expert Systems with Applications, Wireless Personal Communications, CrystEngComm, Knowledge-Based Systems and Education and Information Technologies.

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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