Muyun Yang

48 papers and 259 indexed citations i.

About

Muyun Yang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Muyun Yang has authored 48 papers receiving a total of 259 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Artificial Intelligence, 12 papers in Information Systems and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Muyun Yang’s work include Natural Language Processing Techniques (34 papers), Topic Modeling (29 papers) and Text and Document Classification Technologies (11 papers). Muyun Yang is often cited by papers focused on Natural Language Processing Techniques (34 papers), Topic Modeling (29 papers) and Text and Document Classification Technologies (11 papers). Muyun Yang collaborates with scholars based in China, Japan and United Kingdom. Muyun Yang's co-authors include Shujie Liu, Sheng Li, Ming Zhou, Mu Li, Kehai Chen, Rui Lin, Tiejun Zhao, Tiejun Zhao, Lemao Liu and Rui Wang and has published in prestigious journals such as IEEE Access, Information Sciences and IEEE Transactions on Fuzzy Systems.

In The Last Decade

Co-authorship network of co-authors of Muyun Yang i

Fields of papers citing papers by Muyun Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Muyun Yang

Since Specialization
Citations

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

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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2025