Geunseok Yang

533 total citations
19 papers, 399 citations indexed

About

Geunseok Yang is a scholar working on Information Systems, Software and Computer Networks and Communications. According to data from OpenAlex, Geunseok Yang has authored 19 papers receiving a total of 399 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Information Systems, 9 papers in Software and 8 papers in Computer Networks and Communications. Recurrent topics in Geunseok Yang's work include Software Engineering Research (19 papers), Software System Performance and Reliability (8 papers) and Software Reliability and Analysis Research (7 papers). Geunseok Yang is often cited by papers focused on Software Engineering Research (19 papers), Software System Performance and Reliability (8 papers) and Software Reliability and Analysis Research (7 papers). Geunseok Yang collaborates with scholars based in South Korea, Hong Kong and China. Geunseok Yang's co-authors include Byungjeong Lee, Tao Zhang, Jiachi Chen, Xiapu Luo, Jungwon Lee, Alvin Chan, Jungyeon Kim, Eng Keong Lua and Taemin Kim and has published in prestigious journals such as IEEE Access, Applied Sciences and Journal of Systems and Software.

In The Last Decade

Geunseok Yang

18 papers receiving 385 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Geunseok Yang South Korea 10 376 233 143 102 87 19 399
Stéphane Vaucher Canada 7 451 1.2× 343 1.5× 123 0.9× 136 1.3× 90 1.0× 10 478
Hung Viet Nguyen United States 7 282 0.8× 180 0.8× 123 0.9× 45 0.4× 108 1.2× 9 307
Xuan Huo China 9 319 0.8× 212 0.9× 123 0.9× 114 1.1× 77 0.9× 9 336
Claudia Marcos Argentina 10 300 0.8× 179 0.8× 93 0.7× 37 0.4× 104 1.2× 39 325
Ahmed Lamkanfi Belgium 6 494 1.3× 312 1.3× 187 1.3× 126 1.2× 91 1.0× 7 516
Napol Rachatasumrit United States 5 278 0.7× 208 0.9× 78 0.5× 58 0.6× 54 0.6× 9 314
Quinten David Soetens Belgium 8 285 0.8× 215 0.9× 101 0.7× 57 0.6× 51 0.6× 12 304
Kisub Kim Singapore 10 284 0.8× 166 0.7× 68 0.5× 69 0.7× 118 1.4× 28 353
Santiago Vidal Argentina 9 267 0.7× 182 0.8× 116 0.8× 55 0.5× 71 0.8× 26 299
Chu-Pan Wong United States 8 284 0.8× 238 1.0× 83 0.6× 64 0.6× 95 1.1× 10 327

Countries citing papers authored by Geunseok Yang

Since Specialization
Citations

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

Fields of papers citing papers by Geunseok Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Geunseok Yang

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

All Works

19 of 19 papers shown
1.
Yang, Geunseok, et al.. (2025). Leveraging Cross-Project Similarity for Data Augmentation and Security Bug Report Prediction. IEEE Access. 13. 80416–80428.
2.
Yang, Geunseok, et al.. (2023). Applying Multitopic Analysis of Bug Reports and CNN algorithm to Bug Severity Prediction. Journal of KIISE. 50(11). 954–965. 1 indexed citations
3.
Kim, Taemin & Geunseok Yang. (2022). Predicting Duplicate in Bug Report Using Topic-Based Duplicate Learning With Fine Tuning-Based BERT Algorithm. IEEE Access. 10. 129666–129675. 7 indexed citations
4.
Kim, Jungyeon & Geunseok Yang. (2022). Bug Severity Prediction Algorithm Using Topic-Based Feature Selection and CNN-LSTM Algorithm. IEEE Access. 10. 94643–94651. 18 indexed citations
5.
Yang, Geunseok, et al.. (2022). A Bug Triage Technique Using Developer-Based Feature Selection and CNN-LSTM Algorithm. Applied Sciences. 12(18). 9358–9358. 6 indexed citations
6.
Yang, Geunseok & Byungjeong Lee. (2021). Utilizing Topic-Based Similar Commit Information and CNN-LSTM Algorithm for Bug Localization. Symmetry. 13(3). 406–406. 7 indexed citations
7.
Yang, Geunseok, et al.. (2020). Applying deep learning algorithm to automatic bug localization and repair. 1634–1641. 13 indexed citations
8.
Yang, Geunseok, et al.. (2019). Applying Topic Modeling and Similarity for Predicting Bug Severity in Cross Projects. KSII Transactions on Internet and Information Systems. 13(3). 6 indexed citations
9.
Yang, Geunseok, Tao Zhang, & Byungjeong Lee. (2018). An Emotion Similarity Based Severity Prediction of Software Bugs: A Case Study of Open Source Projects. IEICE Transactions on Information and Systems. E101.D(8). 2015–2026. 14 indexed citations
10.
Yang, Geunseok, et al.. (2017). Analyzing emotion words to predict severity of software bugs. 1280–1287. 25 indexed citations
11.
Yang, Geunseok, et al.. (2016). Bug Severity Prediction by Classifying Normal Bugs with Text and Meta-Field Information. Advanced science and technology letters. 19–24. 10 indexed citations
12.
Zhang, Tao, Geunseok Yang, Byungjeong Lee, & Alvin Chan. (2016). Guiding Bug Triage through Developer Analysis in Bug Reports. International Journal of Software Engineering and Knowledge Engineering. 26(3). 405–431. 5 indexed citations
13.
Yang, Geunseok, et al.. (2016). Improving predictions about bug severity by utilizing bugs classified as normal. Contemporary Engineering Sciences. 9. 933–942. 9 indexed citations
14.
Zhang, Tao, Jiachi Chen, Geunseok Yang, Byungjeong Lee, & Xiapu Luo. (2016). Towards more accurate severity prediction and fixer recommendation of software bugs. Journal of Systems and Software. 117. 166–184. 118 indexed citations
15.
Yang, Geunseok & Byungjeong Lee. (2015). Predicting Bug Severity by utilizing Topic Model and Bug Report Meta-Field. KIISE Transactions on Computing Practices. 21(9). 616–621. 1 indexed citations
16.
Zhang, Tao, Geunseok Yang, Byungjeong Lee, & Alvin Chan. (2015). Predicting severity of bug report by mining bug repository with concept profile. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 1553–1558. 33 indexed citations
17.
Zhang, Tao, Geunseok Yang, Byungjeong Lee, & Eng Keong Lua. (2014). A Novel Developer Ranking Algorithm for Automatic Bug Triage Using Topic Model and Developer Relations. 223–230. 31 indexed citations
18.
Yang, Geunseok, Tao Zhang, & Byungjeong Lee. (2014). Utilizing a multi-developer network-based developer recommendation algorithm to fix bugs effectively. 1134–1139. 10 indexed citations
19.
Yang, Geunseok, Tao Zhang, & Byungjeong Lee. (2014). Towards Semi-automatic Bug Triage and Severity Prediction Based on Topic Model and Multi-feature of Bug Reports. 97–106. 85 indexed citations

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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