Feng-Hsu Wang

754 total citations · 1 hit paper
28 papers, 548 citations indexed

About

Feng-Hsu Wang is a scholar working on Information Systems, Artificial Intelligence and Computer Science Applications. According to data from OpenAlex, Feng-Hsu Wang has authored 28 papers receiving a total of 548 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Information Systems, 13 papers in Artificial Intelligence and 11 papers in Computer Science Applications. Recurrent topics in Feng-Hsu Wang's work include Online Learning and Analytics (8 papers), Intelligent Tutoring Systems and Adaptive Learning (6 papers) and Recommender Systems and Techniques (6 papers). Feng-Hsu Wang is often cited by papers focused on Online Learning and Analytics (8 papers), Intelligent Tutoring Systems and Adaptive Learning (6 papers) and Recommender Systems and Techniques (6 papers). Feng-Hsu Wang collaborates with scholars based in Taiwan. Feng-Hsu Wang's co-authors include Shyong Jian Shyu, Chih‐Ming Lin and Ching‐Chi Hsu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Computers & Education.

In The Last Decade

Feng-Hsu Wang

22 papers receiving 514 citations

Hit Papers

An exploration of online behaviour engagement and achieve... 2017 2026 2020 2023 2017 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. An exploration of online behaviour engagement and achievement in flipped classroom supported by learning management system
    2017 186 citations Feng-Hsu Wang profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Feng-Hsu Wang Taiwan 11 230 226 207 107 106 28 548
Séamus Lawless Ireland 11 90 0.4× 283 1.3× 210 1.0× 250 2.3× 113 1.1× 73 680
Jane Yin-Kim Yau United Kingdom 15 196 0.9× 242 1.1× 346 1.7× 109 1.0× 116 1.1× 51 721
Zhiting Zhu China 9 191 0.8× 229 1.0× 147 0.7× 68 0.6× 71 0.7× 26 552
Fattaneh Taghiyareh Iran 12 76 0.3× 137 0.6× 113 0.5× 141 1.3× 120 1.1× 91 477
Panagiotis Zervas Greece 12 127 0.6× 211 0.9× 221 1.1× 77 0.7× 87 0.8× 80 589
Diana Pérez-Marín Spain 15 138 0.6× 194 0.9× 386 1.9× 288 2.7× 244 2.3× 72 701
Gilbert Paquette Canada 13 145 0.6× 179 0.8× 302 1.5× 216 2.0× 159 1.5× 82 618
Islam Taj-Eddin Egypt 10 211 0.9× 154 0.7× 45 0.2× 80 0.7× 34 0.3× 30 486
Giuseppina Rita Mangione Italy 11 122 0.5× 97 0.4× 125 0.6× 121 1.1× 100 0.9× 79 408
Shakeel Khoja Pakistan 12 140 0.6× 113 0.5× 114 0.6× 232 2.2× 43 0.4× 42 532

Countries citing papers authored by Feng-Hsu Wang

Since Specialization
Citations

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

Fields of papers citing papers by Feng-Hsu Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng-Hsu Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Feng-Hsu Wang. A scholar is included among the top collaborators of Feng-Hsu Wang 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 Feng-Hsu Wang. Feng-Hsu Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Wang, Feng-Hsu. (2023). Efficient generation of text feedback in object-oriented programming education using cached performer revision. SHILAP Revista de lepidopterología. 13. 100481–100481. 4 indexed citations
3.
Wang, Feng-Hsu. (2022). A Feasible Study of a Deep Learning Model Supporting Human–Machine Collaborative Learning of Object-Oriented Programming. IEEE Transactions on Learning Technologies. 17. 413–427. 9 indexed citations
4.
Wang, Feng-Hsu & Chih‐Ming Lin. (2020). The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics. International Journal of Environmental Research and Public Health. 17(24). 9288–9288. 8 indexed citations
5.
Wang, Feng-Hsu. (2019). On Prediction of Online Behaviors and Achievement Using Self-regulated Learning Awareness in Flipped Classrooms. International Journal of Information and Education Technology. 9(12). 874–879. 13 indexed citations
6.
7.
Wang, Feng-Hsu, et al.. (2011). A new entity similarity measurement based on automatic featuring for ontology mapping. 84–89.
8.
Wang, Feng-Hsu. (2011). Design of an Online Diagnostic Test Tool for Personalized Learning Based on Componential IRT Approach. 3(2). 99–122. 2 indexed citations
9.
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Wang, Feng-Hsu. (2008). Content Recommendation Based on Education-Contextualized Browsing Events for Web-based Personalized Learning. Educational Technology & Society. 11(4). 94–112. 26 indexed citations
11.
Wang, Feng-Hsu, et al.. (2008). A Knowledge Integration Framework for Adaptive Learning Systems Based on Semantic Web Languages. 5. 64–68. 5 indexed citations
12.
Wang, Feng-Hsu. (2007). On discovery of soft associations with “most” fuzzy quantifier for item promotion applications. Information Sciences. 178(7). 1848–1876. 16 indexed citations
13.
14.
Wang, Feng-Hsu, et al.. (2004). Effective personalized recommendation based on time-framed navigation clustering and association mining. Expert Systems with Applications. 27(3). 365–377. 116 indexed citations
15.
Wang, Feng-Hsu. (2003). A fuzzy neural network for item sequencing in personalized cognitive scaffolding with adaptive formative assessment. Expert Systems with Applications. 27(1). 11–25. 9 indexed citations
16.
Wang, Feng-Hsu. (2002). On Using Data-Mining Technology for Browsing Log File Analysis in Asynchronous Learning Environment. EdMedia: World Conference on Educational Media and Technology. 2002(1). 2005–2006. 10 indexed citations
17.
Wang, Feng-Hsu. (1998). On the design of an intelligent exploratory environment for geographic climates on WWW. Computer Networks and ISDN Systems. 30(1-7). 699–700.
18.
Wang, Feng-Hsu, et al.. (1997). On routing maskable messages in hypercube-derived multistage interconnection networks. IEEE Transactions on Parallel and Distributed Systems. 8(3). 285–291.
19.
Wang, Feng-Hsu, et al.. (1993). On constructing multiple spanning trees in a hypercube. Information Processing Letters. 45(4). 177–183. 3 indexed citations
20.
Hsu, Ching‐Chi & Feng-Hsu Wang. (1989). The search ahead conflict resolution for parallel firing of production systems. International Joint Conference on Artificial Intelligence. 24(13). 91–96.

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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