Journal Papers

1. [In preparation] HIVE+: Extending Human-In-the-Loop Explainable Recommendation with Collective Novelty and Veracity Alignment. Yeonbin Son and Matthew L. Bolton*. 

2. [Under review] Veracity: An Objective Signal Detection Measure for Evaluating the Information Quality of Recommender System Explanations. Yeonbin Son and Matthew L. Bolton*. Submitted to ACM Transactions on Recommender Systems.

3. [Under review] MVStyle: Multi-view Contrastive Learning for Fashion Style Classification. Yeonbin Son, Jonghyuk Park, Jonghun Park, and Yerim Choi*. Submitted to Information Processing & Management.

4. Omnichannel Strategy Development Framework: Analyzing Opinion Divergence via Integrated LLM and XAI. Bohyun Choi, Yeonbin Son (co-1st), and Yerim Choi*. Accepted to Scientific Reports. paper

5. Enhancing Fashion Style Classification by Capturing Local Details. Yeonbin Son, Jinhyun Bang, Jonghyuk Park, Jonghun Park, and Yerim Choi*. Expert Systems with Applications, Vol.306, 130849 (2026). paper

6. Validation of a Formal Method for Human Error Rate Prediction with Negative Transfer. Yeonbin Son, Matthew L. Bolton*, Emma Crooks, Hannah Palmer, Eunsuk Kang, and Christopher Daly. IEEE Transactions on Human-Computer Systems, Vol.55, No.5, pp.844-854 (2025). paper

7. Data-Driven Policy Making Framework Based on TOWS Analysis. Yeonbin Son, Youngeun Kim, and Yerim Choi*. IEEE Access, Vol.13, pp.93786-93797 (2025). paper

8. Determining Optimal Assembly Condition for Lens Module Production by Combining Genetic Algorithm and C-BLSTM. Hyegeun Min, Yeonbin Son (co-1st), and Yerim Choi*. Processes, Vol.12, No.3, p.452 (2024). paper

9. ICT Trend Analysis Based on Research Papers and Patents. Yeonbin Son, Solha Kim, and Yerim Choi*. Journal of Korea Convergence Society, Vol.12, No.12, pp.1-18 (2021). paper

10. Improving Matrix Factorization Based Expert Recommendation for Manuscript Editing Services by Refining User Opinions with Binary Ratings. Yeonbin Son and Yerim Choi*. Applied Sciences, Vol.10, No.3395 (2020). paper

11. (Invited) Dessert Ateliers Recommendation Methods for Dessert E-Commerce Services. Yeonbin Son, Tai-Woo Chang, and Yerim Choi*. Journal of Internet Computing and Services, Vol.21, No.1, pp.111-117 (2020). paper

12. Development of Journal Recommendation Method Considering Importance of Decision Factors Based on Researchers’ Paper Publication History. Yeonbin Son, Tai-Woo Chang, and Yerim Choi*. Journal of Internet Computing and Services, Vol.20, No.4, pp.73-79 (2019). paper

13. A Proofreader Matching Method Based on Topic Modeling Using the Importance of Documents. Yeonbin Son, Hyeontae An, and Yerim Choi*. Journal of Internet Computing and Services, Vol.19, No.4, pp.27-33 (2018). paper

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Conference Papers

1. HIVE: Human-in-the-Loop Framework for Explainable Recommender Systems with Veracity-Based Human Feedback. Yeonbin Son, Bohyun Choi, Jiyoun Park, Yerim Choi, and Matthew L. Bolton*. CIKM 2025 Workshop on Human-Centric AI (HCAI).

2. Towards a Signal Detection Based Measure for Assessing Information Quality of Explainable Recommender Systems. Yeonbin Son and Matthew L. Bolton*. Proceedings of IEEE Conference on Artificial Intelligence, Santa Clara, CA, USA, May. 5-7 (2025). paper

3. Negative Transfer in Task-Based Human Reliability Analysis: A Formal Methods Approach. Matthew L. Bolton*, Svetlana Riabova, Yeonbin Son, and Eunsuk Kang. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, Oahu, HI, USA, Oct. 1-4 (2023). paper

4. Dynamic Learning of User Preference Based on Path-level Feedback for Knowledge Graph-based Recommender Systems. Yeonbin Son, Sunghoon Kim, Hyewon Seo, Yewon Kang, and Yerim Choi*. 2022 The Institute for Operations Research and the Management Sciences (INFORMS) Annual Meeting, Indianapolis, IN, USA, Oct. 16-19 (2022).

5. Incremental Learning Framework of Knowledge Graph Based on User Preference for Conversational Recommender System. Sunghoon Kim, Yeonbin Son, Solha Kim, and Yerim Choi*. Proceedings of the Korean Information Science Society Conference, Jeju, South Korea, Jun. (2022).

6. Dessert Atelier Recommender System Based On Tensor Factorization Using Multiple User Feedbacks. Yeonbin Son, Eunyoung Choi, Younghoon Roh, Sunghoon Kim, and Yerim Choi*. 2020 The Institute for Operations Research and the Management Sciences (INFORMS) Annual Meeting, Online, Nov. 8-11 (2020) – Oral. 

7. Improving Journal Recommender Systems with Dynamic Weighting Methods. Yeonbin Son, Sunghoon Kim, and Yerim Choi*. Institute of Industrial and Systems Engineers Annual Conference, Orlando, FL, USA, May. 18-21 (2019) – Oral. 

8. Dessert Atelier Recommendation Method Considering Importance of Visit Decision Factor. Yeonbin Son, Sunghoon Kim, and Yerim Choi*. International Conference on Internet, Hanoi, Vietnam, Dec. 16-19 (2018) – Oral. 

9. A Clustering-Based Recommendation Method for Dessert Ateliers Considering Purchase History of Customers. Yeonbin Son, Eunyoung Choi, Younghoon Roh, and Yerim Choi*. Asia Pacific International Conference on Information Science and Technology, Nha Trang, Vietnam, Jun. 24-27 (2018) – Oral. 

10. (Excellent Paper Award) An Editor Recommendation Method for Manuscript Proofreading Services Considering Specialty and Influence of Editor. Yeonbin Son, Hyeontae An, Jaemyoung Choi, and Yerim Choi*. International Symposium on Innovation in Information Technology Application, Kota Kinabalu, Malaysia, Jan. 30 – Feb. 2 (2018) – Oral. 

11. (Best Paper Award) A Dynamic Weighting Based Journal Recommendation Method Considering Researchers’ Submission Record. Yeonbin Son, Younghoon Roh, Sunghoon Kim, and Yerim Choi*. Fall Conference of The Korean Society for Internet Information, Seoul, Korea, Nov. 2-3 (2018) – Oral. 

12. LDA Based Journal Recommendation Method by Extracting Topics of Researchers and Journals. Yeonbin Son, Yejun Lee, Sooyoun Kim, Jaemyoung Choi, Jonghwan Lee, Jinyoung Jang, and Yerim Choi*. Spring Conference of The Korean Society for Internet Information, Jeju, Korea, Apr. 27-28 (2018) – Oral. 

13. (Best Paper Award) LDA based Expert Matching Method Considering Importance of Documents. Hyeontae An, Yeonbin Son, Hyejoo Park, and Yerim Choi*. Fall Conference of The Korean Society for Internet Information, Seoul, Korea, Nov. 3-4 (2017) – Oral. 

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Patents

• Explainable Recommender System and Method based on Knowledge Graph Leveraging Dynamic Weight on Multi-hop Relations.

  • Yeonbin Son, Sunghoon Kim, Solha Kim, Yewon Kang, Hyewon Seo, and Yongsuk Yang

  • Korea – Registration No. 10-2022-0032013 (2022.03.15).

• Method and System With Optimization of Lens Module Assembly.

  • Hyegeun Min, Yerim Choi, Yeonbin Son, Sunghoon Kim, and Eunyoung Choi.

  • Achievement of the project collaboration with Samsung Electro-Mechanics

  • Korea – Application No. 10-2021-0023177 (2021.02.22).

  • United States – Application No. 17/397,136.

  • China – Application No. 202111268807.X

• System and Method for Providing Hierarchical Information Search Graphic User Interface based on Word-Cloud.

  • Yerim Choi, Yeonbin Son, Yejoon Lee, Suyeon Kim, and Eunyoung Choi.

  • Korea – Registration No. 10-2158-1940000 (2020.09.15).

• Apparatus and Method for Recommending Editor.

  • Yerim Choi, Yeonbin Son, Hyeontae An, Hyejoo Park, Jonghwan Lee, and Jinyoung Jang.

  • Korea – Registration No. 10-2036-5070000 (2019.10.21).

• Item Recommendation Method Based on Preference Sensitivity over Purchase Decision Factor.

  • Yerim Choi and Yeonbin Son.

  • Korea – Application No. 10-2018-0160130 (2018.12.12).