Publications
Research on recommender systems, graph learning, network alignment, and explainable AI.
International publications
Memory is No Longer a Bottleneck: Memory-Efficient Graph Filtering for Scalable Collaborative Filtering
Centrality-Based Node Feature Augmentation for Robust Network Alignment
Criteria-Aware Graph Filtering: Extremely Fast Yet Accurate Multi-Criteria Recommendation
Leveraging Member-Group Relations via Multi-View Graph Filtering for Effective Group Recommendation
Turbo-CF: Matrix Decomposition-Free Graph Filtering for Fast Recommendation
Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order Connectivity
Criteria Tell You More Than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation
On the Power of Gradual Network Alignment Using Dual-Perception Similarities
GradAlign+: Empowering Gradual Network Alignment Using Attribute Augmentation
Gradual Network Alignment via Graph Neural Network
Explainable Gait Recognition with Prototyping Encoder-Decoder
Two-Stage Deep Anomaly Detection with Heterogeneous Time Series Data for Smart Manufacturing
Node Feature Augmentation Vitaminizes Network Alignment
Domestic publications
그래프 신경망을 사용한 다 기준 추천 알고리즘
점진적 네트워크 정렬
Empowering Gradual Network Alignment Using Attribute Augmentation
Gradual Network Alignment with Edge Augmentation
스마트 공정에 필요한 이상 탐지 방법에 대한 포괄적 실험 연구
심층 발걸음 인식 모델에 대한 설명 가능한 인공지능
제조업에서의 심층 이상 탐지
확장 그래프에서의 그래프 신경망을 활용한 다 기준 추천시스템
Sophisticated Graph Filter Design for Accurate Recommendation
물리인지 그래프 학습 기반 인공지능을 통한 실시간 유방암 위치 예측
물리인지 그래프 네트워크를 활용한 실시간 유방암 위치 모니터링
기계학습을 활용한 네트워크 정렬 기술 최근 동향