Min‐Yen Kan

150 papers and 3.3k indexed citations i.

About

Min‐Yen Kan is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Min‐Yen Kan has authored 150 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 111 papers in Artificial Intelligence, 25 papers in Information Systems and 21 papers in Computer Vision and Pattern Recognition. Recurrent topics in Min‐Yen Kan’s work include Topic Modeling (89 papers), Natural Language Processing Techniques (73 papers) and Advanced Text Analysis Techniques (25 papers). Min‐Yen Kan is often cited by papers focused on Topic Modeling (89 papers), Natural Language Processing Techniques (73 papers) and Advanced Text Analysis Techniques (25 papers). Min‐Yen Kan collaborates with scholars based in Singapore, United States and China. Min‐Yen Kan's co-authors include Xiangnan He, Tat‐Seng Chua, Hanwang Zhang, Kazunari Sugiyama, Ziheng Lin, Hwee Tou Ng, Su Nam Kim, Timothy Baldwin, Judith L. Klavans and Olena Medelyan and has published in prestigious journals such as Antimicrobial Agents and Chemotherapy, Communications of the ACM and IEEE Access.

In The Last Decade

Co-authorship network of co-authors of Min‐Yen Kan i

Fields of papers citing papers by Min‐Yen Kan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min‐Yen Kan. 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 Min‐Yen Kan. The network helps show where Min‐Yen Kan may publish in the future.

Countries citing papers authored by Min‐Yen Kan

Since Specialization
Citations

This map shows the geographic impact of Min‐Yen Kan'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 Min‐Yen Kan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Min‐Yen Kan 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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