Hello, I’m Hong-Kyun Bae, an assistant professor in the Department of Computer Science at Kookmin University. I earned my B.S. in Computer Science and Engineering from Inha University. In 2023, I had the opportunity to be a visiting scholar at Pennsylvania State University. I completed my Ph.D. in Computer Science from Hanyang University in 2024 under the guidance of Professor Sang-Wook Kim. My research focuses on Recommender Systems, Data Mining, and Artificial Intelligence.
If you are interested in collaborating with me, please feel free to contact me.
Work Experience
Kookmin University
Mar. 2025 -
Assistant Professor at the Department of Computer Science
Hanyang University
Sep. 2024 - Feb. 2025
Postdoctoral Researcher at the Department of Computer Science (PI: Prof. Sang-Wook Kim)
Penn State
Sep. 2023 - Nov. 2023
Visiting Researcher at the College of Information Sciences and Technology (PI: Prof. Dongwon Lee)
Education
Hanyang University
Sep. 2016 - Aug. 2024
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Ph.D. in Computer Science
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Big Data Science Lab (Advisor: Prof. Sang-Wook Kim)
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Thesis: Understanding Domain Characteristics for Effective Learning-to-Rank (LTR) Approaches in Recommender Systems (Outstanding Ph.D. Dissertation Award)
Inha University
Mar. 2009 - Aug. 2016
- B.S. in Computer Science and Engineering
Selected Publications
International Conferences
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Hong-Kyun Bae, Hae-Ri Jang, Won-Yong Shin, and Sang-Wook Kim. “Ranking Items by the Current-Preferences and Profits: A List-wise Learning-to-Rank Approach to Profit Maximization.” ACM WWW (BK21 Top Conference, IF: 4), 2025 (accepted to appear).
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Hong-Kyun Bae, Yebeen Kim, Hyunjoon Kim, and Sang-Wook Kim. “Negative Sampling in Next-POI Recommendations: Observation, Approach, and Evaluation.” ACM WWW (BK21 Top Conference, IF: 4), 2024.
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Hong-Kyun Bae, Hae-Ri Jang, Yang-Sae Moon, and Sang-Wook Kim. “Item-Ranking Promotion in Recommender Systems.” ACM WWW (Short), 2024.
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Jeewon Ahn, Hong-Kyun Bae, and Sang-Wook Kim. “Is the ‘Impression Log’ Beneficial to Evaluating News Recommender Systems? No, it is Not!.” ACM WWW (Short), 2024.
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Jeewon Ahn, Hong-Kyun Bae, and Sang-Wook Kim. “Is the Impression Log Beneficial to Effective Model Training in News Recommender Systems? No, It’s NOT.” ACM WWW (Short), 2023.
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Hong-Kyun Bae, Yeon-Chang Lee, Kyungsik Han, and Sang-Wook Kim. “A Competition-Aware Approach to Accurate TV Show Recommendation.” IEEE ICDE (BK21 Top Conference, IF: 3), 2023.
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Hong-Kyun Bae, Jeewon Ahn, Dongwon Lee, and Sang-Wook Kim. “LANCER: A Lifetime-Aware News Recommender System.” AAAI (BK21 Top Conference, IF: 4), 2023.
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Sung-Jun Park, Dong-Kyu Chae, Hong-Kyun Bae, Sumin Park, and Sang-Wook Kim. “Reinforcement Learning over Sentiment-Augmented Knowledge Graphs towards Accurate and Explainable Recommendation.” ACM WSDM (BK21 Top Conference, IF: 3), 2022.
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Yunyong Ko, Jae-Seo Yu, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, and Sang-Wook Kim. “MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems.” IEEE ICDM (BK21 Top Conference, IF: 3), 2021.
International SCIE Journals
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Hong-Kyun Bae, Jiyeon Kim, Jongwuk Lee, and Sang-Wook Kim. “DUET: Dually Guided Knowledge Distillation from Explicit Feedback.” Information Fusion (JCR 2023 IF: 14.8 (Top 3%)), 2025 (accepted to appear).
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Hong-Kyun Bae, Hyung-Ook Kim, Won-Yong Shin, and Sang-Wook Kim. “How to Get Consensus with Neighbors?: Rating Standardization for Accurate Collaborative Filtering.” Knowledge-Based Systems (JCR 2023 IF: 7.2 (Top 15%)), 2021.
Professional Services
Conference Reviewer
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International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2024.
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ACM Web Conference (WWW), 2024.
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ACM/SIGAPP Symposium On Applied Computing (SAC), 2024–2025.
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IEEE International Conference on Data Mining (ICDM), 2023–2024.
Journal Reviewer
- IEEE Transactions on Services Computing, 2024.