Young D. Kwon

24 papers receiving 399 citations

Peers

Young D. Kwon
Comparison fields: 5 of 77
  • Health Informatics 97
  • Computer Science Applications 90
  • Artificial Intelligence 157
  • Human-Computer Interaction 24
  • Communication 25
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Sarang Shaikh Norway
Marcin Gruza Poland
Konrad Wojtasik Poland
Nayeon Lee Hong Kong
Holy Lovenia Hong Kong
Daphne Ippolito United States
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Citations per year

Countries citing papers authored by Young D. Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Young D. Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young D. Kwon. 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 Young D. Kwon. The network helps show where Young D. Kwon may publish in the future.

Co-authors

The 25 scholars most cited alongside Young D. Kwon, 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 Young D. Kwon Line = papers co-authored together Young D. Kwon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2023212
2 202030
3 202024
4 200618
5 202113
6 201911
7 202211
8 202010
9 201910
10 202210
11 20229
12 20208
13 20238
14 20208
15 20226
16 20215
17 20224
18
Clinical Analysis of Postoperative Prognostic Factors of Cervical Anterior Decompression and Interbody Fusion for Ossification of Posterior Longitudinal Ligament.
20002
19
Statistical Observation on Neonate
19932
20 20182

About Young D. Kwon

Young D. Kwon is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Electrical and Electronic Engineering, having authored 25 papers that have together received 408 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (3 papers), Complex Network Analysis Techniques (3 papers), Social Media and Politics (3 papers), Opinion Dynamics and Social Influence (3 papers), Green IT and Sustainability (2 papers), Advanced Neural Network Applications (2 papers), User Authentication and Security Systems (2 papers) and Hand Gesture Recognition Systems (2 papers). The work is most often cited by research in Health Informatics (97 citations), Computer Science Applications (90 citations), Artificial Intelligence (157 citations), Human-Computer Interaction (24 citations) and Communication (25 citations). Young D. Kwon has collaborated with scholars based in United Kingdom, Hong Kong and Finland. Frequent co-authors include Pan Hui, Cecilia Mascolo, Reza Hadi Mogavi, Jagmohan Chauhan, Antonio Bucchiarone, Chao Deng, Ahmed Hosny Saleh Metwally, Sujit Gujar, Lennart E. Nacke and Ahmed Tlili. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Journal of Korean Neurosurgical Society, IEEE Access, IEEE Transactions on Mobile Computing and Physical Review B.

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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