Wonseok Hwang

2.5k total citations
57 papers, 1.4k citations indexed

About

Wonseok Hwang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Wonseok Hwang has authored 57 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 12 papers in Information Systems and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Wonseok Hwang's work include Recommender Systems and Techniques (10 papers), Natural Language Processing Techniques (7 papers) and Topic Modeling (6 papers). Wonseok Hwang is often cited by papers focused on Recommender Systems and Techniques (10 papers), Natural Language Processing Techniques (7 papers) and Topic Modeling (6 papers). Wonseok Hwang collaborates with scholars based in South Korea, United States and China. Wonseok Hwang's co-authors include Changbong Hyeon, Lawrence R. Sita, Sang‐Wook Kim, Robert M. Briber, Sungchul Hohng, Dongwon Lee, Jongwuk Lee, Stephen J. Banik, Bani H. Cipriano and Renu Sharma and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and Angewandte Chemie International Edition.

In The Last Decade

Wonseok Hwang

54 papers receiving 1.4k citations

Peers

Wonseok Hwang
Comparison fields: 5 of 130
  • Organic Chemistry 246
  • Biomaterials 243
  • Biomedical Engineering 232
  • Molecular Biology 221
  • Artificial Intelligence 209
Replace Yuqing Wu with:
Yuqing Wu China
Kyungmin Lee South Korea
Ching‐Yi Chen Taiwan
Ling Hu China
Donghua Liu China
Wei Ding China
Hyeyoung Park South Korea
Liangwei Yang China
Jonas Gustafsson Sweden
Yuqing Wu China View profile →
Citations per field, relative to Wonseok Hwang
Wonseok Hwang · 1×
Citations per year, relative to Wonseok Hwang
Wonseok Hwang · 1×

Countries citing papers authored by Wonseok Hwang

Since Specialization
Citations

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

Fields of papers citing papers by Wonseok Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wonseok Hwang. 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 Wonseok Hwang. The network helps show where Wonseok Hwang may publish in the future.

Co-authorship network of co-authors of Wonseok Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of Wonseok Hwang. A scholar is included among the top collaborators of Wonseok Hwang 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 Wonseok Hwang. Wonseok Hwang 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
# Work Indexed citations
1 1
2 0
3 32
4
BROS: A Pre-trained Language Model for Understanding Texts in Document
15
5 34
6 20
7 18
8 13
9 37
10 21
11 43
12 2
13 63
14 64
15 1
16 4
17 37
18 13
19 56
20 20

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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