Ming-Che Lee
Impact in
-
- Open Education and E-Learning
- Online Learning and Analytics
- Information Systems top 5%
- Recommender Systems and Techniques
Papers in
-
- Open Education and E-Learning 7
- Online Learning and Analytics 4
-
- Semantic Web and Ontologies 10
- Topic Modeling 7
- Advanced Text Analysis Techniques 7
- Natural Language Processing Techniques 6
- Co-authors
- Tzone I. WangChien‐Yuan SuJia-Wei ChangSheng‐Cheng YehShu‐Yin ChiangDasheng LeeChing‐Hui ChenPo‐Sheng Chiu
- Journals
- Expert Systems with Applications (4 papers)IEEE Access (3 papers)Multimedia Tools and Applications (2 papers)International Journal of Advancements in Computing Technology (2 papers)Computers in Industry (1 paper)
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
Ming-Che Lee
50 papers receiving 646 citations
Peers
Comparison fields: 5 of 90
- Computer Science Applications 192
- Information Systems 247
- Artificial Intelligence 338
- Management Science and Operations Research 91
- Signal Processing 58
Countries citing papers authored by Ming-Che Lee
This map shows the geographic impact of Ming-Che Lee'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 Ming-Che Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming-Che Lee more than expected).
Fields of papers citing papers by Ming-Che Lee
This network shows the impact of papers produced by Ming-Che Lee. 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 Ming-Che Lee. The network helps show where Ming-Che Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming-Che Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2022 | 4 | |
| 6 | 2022 | 33 | |
| 7 | 2021 | 25 | |
| 8 | 2020 | 41 | |
| 9 | 2020 | 39 | |
| 10 | 2020 | 2 | |
| 11 | 2019 | 2 | |
| 12 | 2017 | 3 | |
| 13 | 2016 | 8 | |
| 14 | Designing and implementing a personalized remedial learning system for enhancing the programming learning | 2013 | 32 |
| 15 | 2012 | 3 | |
| 16 | 2009 | 14 | |
| 17 | 2009 | 3 | |
| 18 | 2007 | 52 | |
| 19 | 2006 | 6 | |
| 20 | 2005 | 41 |
About Ming-Che Lee
Ming-Che Lee is a scholar working on Computer Science Applications, Artificial Intelligence, Signal Processing, Management Science and Operations Research and Information Systems, having authored 53 papers that have together received 709 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (10 papers), Topic Modeling (7 papers), Advanced Text Analysis Techniques (7 papers), Open Education and E-Learning (7 papers), Natural Language Processing Techniques (6 papers), Stock Market Forecasting Methods (6 papers), Online Learning and Analytics (4 papers) and Emotion and Mood Recognition (4 papers). The work is most often cited by research in Computer Science Applications (192 citations), Information Systems (247 citations), Artificial Intelligence (338 citations), Management Science and Operations Research (91 citations) and Signal Processing (58 citations). Ming-Che Lee has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Tzone I. Wang, Chien‐Yuan Su, Jia-Wei Chang, Sheng‐Cheng Yeh, Shu‐Yin Chiang, Dasheng Lee, Ching‐Hui Chen, Po‐Sheng Chiu, Xuming Chen and Tsorng-Lin Chia. Their work appears in journals such as Expert Systems with Applications, IEEE Access, Multimedia Tools and Applications, International Journal of Advancements in Computing Technology and Computers in Industry.
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.