데이터 마이닝 연구실

My research interests are large-scale Data Mining and Machine Learning. I lead the development ofPEGASUS (Peta-Scale Graph Mining System), an award-winning open-source software for mining very large graphs in Hadoop and Spark platforms. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) 2026, Jeju, Korea. Jeongin Yun, Jaeri Lee, Jongjin Kim, Minjun Kim, Jinho Song, and U Kang. IEEE International Conference on Data Engineering (ICDE) 2026, Montreal, Canada. Minjun Kim, Jaeri Lee, Jongjin Kim, Jeongin Yun, Yongmo Kwon, and U Kang. Seungcheol Park, Sojin Lee, Jongjin Kim, Jinsik Lee, Hyunjik Jo, and U Kang. Minjun Kim, Jaehyeon Choi, Jongkeun Lee, Wonjin Cho, and U Kang. Seungcheol Park, Jeongin Bae, Beomseok Kwon, Minjun Kim, Byeongwook Kim, Se Jung Kwon, U Kang, and Dongsoo Lee. Minjun Kim, Jaehyeon Choi, SeungJoo Lee, Jinhong Jung, and U Kang. Sequentially Diversified and Accurate Recommendations in Chronological Order for a Series of Users. Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning. Accurate Stock Movement Prediction via Multi-Scale and Multi-Domain Modeling. Towards True Multi-interest Recommendation: Enhanced Scheme for Balanced Interest Training. Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, and Kijung Shin. Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-aware Reranking. Hyunsik Jeon, Jongjin Kim, Jaeri Lee, Jong-eun Lee, and U Kang. Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation. PET: Parameter-efficient Knowledge Distillation on Transformer. Jun-Gi Jang, Sooyeon Shim, Vladimir Egay, Jeeyong Lee, Jongmin Park, Suhyun Chae, and U Kang. Fast and accurate interpretation of workload classification model. Acc