| 2025 | WWW | Ranking Items by the Current-Preferences and Profits: A List-wise Learning-to-Rank Approach to Profit Maximization. | Hong-Kyun Bae, Hae-Ri Jang, Won-Yong Shin, Sang-Wook Kim |
| 2024 | WWW | Is the 'Impression Log' Beneficial to Evaluating News Recommender Systems? No, it is Not! | Jeewon Ahn, Hong-Kyun Bae, Sang-Wook Kim |
| 2024 | WWW | Item-Ranking Promotion in Recommender Systems. | Hong-Kyun Bae, Hae-Ri Jang, Yang-Sae Moon, Sang-Wook Kim |
| 2024 | WWW | Negative Sampling in Next-POI Recommendations: Observation, Approach, and Evaluation. | Hong-Kyun Bae, Yebeen Kim, Hyunjoon Kim, Sang-Wook Kim |
| 2023 | AAAI | LANCER: A Lifetime-Aware News Recommender System. | Hong-Kyun Bae, Jeewon Ahn, Dongwon Lee, Sang-Wook Kim |
| 2023 | ICDE | A Competition-Aware Approach to Accurate TV Show Recommendation. | Hong-Kyun Bae, Yeon-Chang Lee, Kyungsik Han, Sang-Wook Kim |
| 2023 | WWW | Is the Impression Log Beneficial to Effective Model Training in News Recommender Systems? No, It's NOT. | Jeewon Ahn, Hong-Kyun Bae, Sang-Wook Kim |
| 2022 | ICDE | AiRS: A Large-Scale Recommender System at NAVER News. | Hongjun Lim, Yeon-Chang Lee, Jin-Seo Lee, Sanggyu Han, Seunghyeon Kim, Yeon Jeong Jeong, Changbong Kim, Jaehun Kim, Sunghoon Han, Solbi Choi, Hanjong Ko, Dokyeong Lee, Jaeho Choi, Yungi Kim, Hong-Kyun Bae, Taeho Kim, Jeewon Ahn, Hyun-Soung You, Sang-Wook Kim |
| 2022 | WSDM | Reinforcement Learning over Sentiment-Augmented Knowledge Graphs towards Accurate and Explainable Recommendation. | Sung-Jun Park, Dong-Kyu Chae, Hong-Kyun Bae, Sumin Park, Sang-Wook Kim |
| 2021 | ICDM | MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems. | Yun-Yong Ko, Jae-Seo Yu, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, Sang-Wook Kim |