MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems. - Yun-Yong Ko; Jae-Seo Yu; Hong-Kyun Bae; Yongjun Park 001; Dongwon Lee 001; Sang-Wook Kim (ICDM, 2021)

"How to get consensus with neighbors?": Rating standardization for accurate collaborative filtering. - Hong-Kyun Bae; Hyung-Ook Kim; Won-Yong Shin; Sang-Wook Kim (Knowl. Based Syst., 2021)

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; et al. (ICDE, 2022)

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 (WSDM, 2022)

LANCER: A Lifetime-Aware News Recommender System. - Hong-Kyun Bae; Jeewon Ahn; Dongwon Lee 001; Sang-Wook Kim (AAAI, 2023)

A Competition-Aware Approach to Accurate TV Show Recommendation. - Hong-Kyun Bae; Yeon-Chang Lee; Kyungsik Han; Sang-Wook Kim (ICDE, 2023)

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 (WWW (Companion Volume), 2023)

Is the 'Impression Log' Beneficial to Evaluating News Recommender Systems? No, it is Not! - Jeewon Ahn; Hong-Kyun Bae; Sang-Wook Kim (WWW (Companion Volume), 2024)

Item-Ranking Promotion in Recommender Systems. - Hong-Kyun Bae; Hae-Ri Jang; Yang-Sae Moon; Sang-Wook Kim (WWW (Companion Volume), 2024)

Negative Sampling in Next-POI Recommendations: Observation, Approach, and Evaluation. - Hong-Kyun Bae; Yebeen Kim; Hyunjoon Kim; Sang-Wook Kim (WWW, 2024)

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 (WWW, 2025)

DUET: Dually guided knowledge distillation from explicit feedback. - Hong-Kyun Bae; Jiyeon Kim; Jongwuk Lee; Sang-Wook Kim (Inf. Fusion, 2025)