Hyunchul Ahn

2.5k total citations
105 papers, 1.8k citations indexed

About

Hyunchul Ahn is a scholar working on Information Systems, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, Hyunchul Ahn has authored 105 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Information Systems, 28 papers in Artificial Intelligence and 19 papers in Sociology and Political Science. Recurrent topics in Hyunchul Ahn's work include Technology Adoption and User Behaviour (18 papers), Recommender Systems and Techniques (14 papers) and Technology and Data Analysis (12 papers). Hyunchul Ahn is often cited by papers focused on Technology Adoption and User Behaviour (18 papers), Recommender Systems and Techniques (14 papers) and Technology and Data Analysis (12 papers). Hyunchul Ahn collaborates with scholars based in South Korea, United States and Latvia. Hyunchul Ahn's co-authors include Kyoung-jae Kim, Ki Soo Kim, Ingoo Han, Kee-Young Kwahk, Sangjae Lee, Seung Ryul Jeong, H. W. Lee, Kyoungdoug Min, Hyungmook Kang and Young U. Ryu and has published in prestigious journals such as Chemical Engineering Journal, Nano Energy and Computers in Human Behavior.

In The Last Decade

Hyunchul Ahn

88 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hyunchul Ahn South Korea 25 589 443 285 231 199 105 1.8k
Michael Chui United Kingdom 18 311 0.5× 373 0.8× 182 0.6× 357 1.5× 120 0.6× 44 3.1k
Chih‐Hung Wu Taiwan 25 566 1.0× 315 0.7× 614 2.2× 110 0.5× 83 0.4× 97 2.6k
Charles V. Trappey Taiwan 28 481 0.8× 229 0.5× 334 1.2× 182 0.8× 112 0.6× 170 3.0k
Jerome Yen Hong Kong 22 368 0.6× 193 0.4× 215 0.8× 172 0.7× 116 0.6× 89 1.4k
Hemant Jain United States 25 475 0.8× 630 1.4× 132 0.5× 403 1.7× 339 1.7× 114 2.0k
Stijn Viaene Belgium 25 1.2k 2.0× 442 1.0× 300 1.1× 195 0.8× 102 0.5× 102 3.0k
Emmanuel Sirimal Silva United Kingdom 24 434 0.7× 378 0.9× 498 1.7× 401 1.7× 119 0.6× 67 2.4k
Stephen Shaoyi Liao Hong Kong 26 871 1.5× 660 1.5× 229 0.8× 759 3.3× 479 2.4× 120 2.6k
Shuai Zhang China 32 749 1.3× 243 0.5× 485 1.7× 184 0.8× 86 0.4× 172 3.7k

Countries citing papers authored by Hyunchul Ahn

Since Specialization
Citations

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

Fields of papers citing papers by Hyunchul Ahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyunchul Ahn

This figure shows the co-authorship network connecting the top 25 collaborators of Hyunchul Ahn. A scholar is included among the top collaborators of Hyunchul Ahn 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 Hyunchul Ahn. Hyunchul Ahn 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.
Tang, Zhenya, et al.. (2024). A Systematic Literature Review of Privacy Information Disclosure in AI-Integrated Internet of Things (IoT) Technologies. Sustainability. 17(1). 8–8. 1 indexed citations
2.
Lee, Yun‐Ju, Jaejun Lee, & Hyunchul Ahn. (2021). Improvement of a Product Recommendation Model using Customers' Search Patterns and Product Details. Journal of the Korea Society of Computer and Information. 26(1). 265–274.
3.
Lee, Yun‐Ju, et al.. (2020). A Hybrid Collaborative Filtering-based Product Recommender System using Search Keywords. Journal of Intelligence and Information Systems. 26(1). 151–166. 7 indexed citations
4.
Ahn, Hyunchul, et al.. (2019). A Study on Wearable Healthcare Device Adoption : An Integrated Approach of UTAUT2 and MIR. Journal of Information Systems. 28(3). 159–202. 3 indexed citations
5.
Ahn, Hyunchul, et al.. (2019). A Recidivism Prediction Model Based on XGBoost Considering Asymmetric Error Costs. Journal of Intelligence and Information Systems. 25(1). 127–137. 1 indexed citations
6.
Ahn, Hyunchul, et al.. (2019). A Study on the Effect of the Document Summar ization Technique on the Fake News Detection Model. Journal of Intelligence and Information Systems. 25(3). 201–220. 2 indexed citations
7.
Ahn, Hyunchul, et al.. (2019). A Machine Learning-Based Vocational Training Dropout Prediction Model Considering Structured and Unstructured Data. The Journal of the Korea Contents Association. 19(1). 1–15. 1 indexed citations
8.
Ahn, Hyunchul, et al.. (2018). A Hybrid Recommender System based on Collaborative Filtering with Selective Use of Overall and Multicriteria Ratings. Journal of Intelligence and Information Systems. 24(2). 85–109. 3 indexed citations
9.
Ahn, Hyunchul, et al.. (2018). Application of Random Over Sampling Examples(ROSE) for an Effective Bankruptcy Prediction Model. The Journal of the Korea Contents Association. 18(8). 525–535. 2 indexed citations
10.
Ahn, Hyunchul, et al.. (2018). Fake News Detection for Korean News Using Text Mining and Machine Learning Techniques. 25(1). 19–32. 6 indexed citations
11.
Ahn, Hyunchul, et al.. (2018). A Time Series Graph based Convolutional Neural Network Model for Effective Input Variable Pattern Learning : Application to the Prediction of Stock Market. Journal of Intelligence and Information Systems. 24(1). 167–181. 2 indexed citations
12.
13.
Ahn, Hyunchul, et al.. (2017). Roles of Buyer's Trust and Distrust in Open Markets: Focusing on Transfer between Intermediary and Seller. The Journal of the Korea Contents Association. 17(2). 360–374. 2 indexed citations
14.
Ahn, Hyunchul, et al.. (2011). Optimization of Support Vector Machines for Financial Forecasting. Journal of Intelligence and Information Systems. 17(4). 241–254. 4 indexed citations
15.
16.
Kim, Sun Woong & Hyunchul Ahn. (2010). Development of an Intelligent Trading System Using Support Vector Machines and Genetic Algorithms. Journal of Intelligence and Information Systems. 16(1). 71–92. 4 indexed citations
17.
Ahn, Hyunchul & Kyoung-jae Kim. (2007). Breast Cytology Diagnosis using a Hybrid Case-based Reasoning and Genetic Algorithms Approach. 389–398.
18.
Han, Ingoo, et al.. (2006). Optimization of Case-based Reasoning Systems using Genetic Algorithms: Application to Korean Stock Market. Asia Pacific Journal of Information Systems. 16(1). 71–84. 1 indexed citations
19.
Kim, Kyoung-jae & Hyunchul Ahn. (2005). Hybrid Case-based Reasoning and Genetic Algorithms Approach for Customer Classification. Journal of information and communication convergence engineering. 3(4). 209–212. 1 indexed citations
20.
Ahn, Hyunchul, Kyoung-jae Kim, & Ingoo Han. (2005). Simultaneous Optimization Model of Case-Based Reasoning for Effective Customer Relationship Management. Journal of Intelligence and Information Systems. 11(2). 175–195.

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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