Yu‐Shan Shih
- Artificial Intelligence top 1%
- Information Systems top 2%
- Statistics and Probability top 2%
- Computer Vision and Pattern Recognition top 5%
- Computational Theory and Mathematics top 5%
- Co-authors
- Wei‐Yin LohLi-Ling ChuangHyunjoong KimProbal ChaudhuriGrace S. ShiehYu‐Chi HoWei‐Ju LeeSelina C. Wang
- Topics
- Data Mining Algorithms and Applications (8 papers)Rough Sets and Fuzzy Logic (7 papers)Advanced Statistical Methods and Models (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaMachine LearningLWT
- Partner nations
- TaiwanUnited StatesIndia
In The Last Decade
Yu‐Shan Shih
20 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Artificial Intelligence 841
- Information Systems 412
- Statistics and Probability 179
- Computer Vision and Pattern Recognition 157
- Computational Theory and Mathematics 155
Countries citing papers authored by Yu‐Shan Shih
This map shows the geographic impact of Yu‐Shan Shih'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 Yu‐Shan Shih with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu‐Shan Shih more than expected).
Fields of papers citing papers by Yu‐Shan Shih
This network shows the impact of papers produced by Yu‐Shan Shih. 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 Yu‐Shan Shih. The network helps show where Yu‐Shan Shih may publish in the future.
Co-authorship network of co-authors of Yu‐Shan Shih
This figure shows the co-authorship network connecting the top 25 collaborators of Yu‐Shan Shih. A scholar is included among the top collaborators of Yu‐Shan Shih 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 Yu‐Shan Shih. Yu‐Shan Shih is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 61 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | Split Selection Methods for Regression Tree on Detecting Regional Economic Convergence | 0 |
| 8 | 4 | |
| 9 | 24 | |
| 10 | 32 | |
| 11 | 8 | |
| 12 | 5 | |
| 13 | 13 | |
| 14 | QUEST User Manual | 9 |
| 15 | 36 | |
| 16 | 35 | |
| 17 | 12 | |
| 18 | A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithmsbreakdown → | 782 |
| 19 | 61 | |
| 20 | SPLIT SELECTION METHODS FOR CLASSIFICATION TREESbreakdown → | 677 |
About Yu‐Shan Shih
Yu‐Shan Shih is a scholar working on Statistics and Probability, Computational Theory and Mathematics and Management Science and Operations Research, having authored 21 papers that have together received 1.8k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (8 papers), Rough Sets and Fuzzy Logic (7 papers) and Advanced Statistical Methods and Models (5 papers). The work is most often cited by research in Artificial Intelligence (841 citations), Statistics and Probability (179 citations) and Information Systems (412 citations). Yu‐Shan Shih has collaborated with scholars based in Taiwan, United States and India. Frequent co-authors include Wei‐Yin Loh, Li-Ling Chuang, Hyunjoong Kim, Probal Chaudhuri, Grace S. Shieh, Yu‐Chi Ho, Wei‐Ju Lee, Selina C. Wang and Feng‐Chang Lin. Their work appears in journals such as SHILAP Revista de lepidopterología, Machine Learning and LWT.
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.