Ching-Yao Wang

21 papers receiving 366 citations

Peers

Ching-Yao Wang
Comparison fields: 5 of 48
  • Information Systems 267
  • Computational Theory and Mathematics 177
  • Signal Processing 68
  • Artificial Intelligence 185
  • Industrial and Manufacturing Engineering 38
Replace Vincent Naessens with:
Vincent Naessens Belgium
Michael Yu Zhu United States
Jarir K. Chaar United States
Chuck Weinstock United States
Phillip G. Bradford United States
Enn Tyugu Estonia
Kassem A. Saleh Kuwait
Michael R. Poppleton United Kingdom
Jean-Pierre Courtiat France
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Citations per field
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Citations per year

Countries citing papers authored by Ching-Yao Wang

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Yao Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Yao Wang. 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 Ching-Yao Wang. The network helps show where Ching-Yao Wang may publish in the future.

Co-authors

The 18 scholars most cited alongside Ching-Yao Wang, 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 Ching-Yao Wang Line = papers co-authored together Ching-Yao Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001124
2 200571
3 201035
4 201025
5 200917
6 200915
7 200413
8 200212
9 200712
10 200212
11
A content management scheme in a SCORM compliant learning object repository
20059
12 20108
13 20208
14 20217
15 20026
16 20093
17 20163
18 20103
19
Online generation of association rules under multi-dimensional consideration based on negative-border
20073
20 20032

About Ching-Yao Wang

Ching-Yao Wang is a scholar working on Information Systems, Computational Theory and Mathematics, Signal Processing, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 21 papers that have together received 390 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (12 papers), Rough Sets and Fuzzy Logic (9 papers), Data Management and Algorithms (5 papers), Context-Aware Activity Recognition Systems (5 papers), IoT and Edge/Fog Computing (2 papers), Ga2O3 and related materials (2 papers), Algorithms and Data Compression (2 papers) and Imbalanced Data Classification Techniques (2 papers). The work is most often cited by research in Information Systems (267 citations), Computational Theory and Mathematics (177 citations), Signal Processing (68 citations), Artificial Intelligence (185 citations) and Industrial and Manufacturing Engineering (38 citations). Ching-Yao Wang has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Tzung-Pei Hong, Yu‐Hui Tao, Shian‐Shyong Tseng, David C. Yen, Shing‐Han Li, Wenhui Lu, Li‐Chen Fu, Shih-Shinh Huang, Ching-Hu Lu and Jerry Chun‐Wei Lin. Their work appears in journals such as Expert Systems with Applications, IEEE Journal of the Electron Devices Society, Journal of Medical Systems, International Journal of Information Technology & Decision Making and Lecture notes in computer science.

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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