A Novel Privacy-Preserved Recommender System Framework based on Federated Learning. - Jiangcheng Qin; Baisong Liu (CoRR, 2020)

An Explainable Person-Job Fit Model Incorporating Structured Information. - Yunchong Zhang; Baisong Liu; Jiangbo Qian; Jiangcheng Qin; Xueyuan Zhang; Xueyong Jiang (IEEE BigData, 2021)

A Novel Privacy-Preserved Recommender System Framework Based On Federated Learning. - Jiangcheng Qin; Baisong Liu; Jiangbo Qian (ICSIM, 2021)

Ranking-based Federated POI Recommendation with Geographic Effect. - Qian Dong; Baisong Liu; Xueyuan Zhang; Jiangcheng Qin; Bingyuan Wang; Jiangbo Qian (IJCNN, 2022)

FedNCF: Federated Neural Collaborative Filtering for Privacy-preserving Recommender System. - Xueyong Jiang; Baisong Liu; Jiangcheng Qin; Yunchong Zhang; Jiangbo Qian (IJCNN, 2022)

Exploiting high-order behaviour patterns for cross-domain sequential recommendation. - Bingyuan Wang; Baisong Liu; Hao Ren; Xueyuan Zhang; Jiangcheng Qin; Qian Dong; Jiangbo Qian (Connect. Sci., 2022)

Split Two-Tower Model for Efficient and Privacy-Preserving Cross-device Federated Recommendation. - Jiangcheng Qin; Baisong Liu; Xueyuan Zhang; Jiangbo Qian (CoRR, 2022)

Revisiting Data Poisoning Attacks on Deep Learning Based Recommender Systems. - Zhiye Wang; Baisong Liu; Chennan Lin; Xueyuan Zhang; Ce Hu; Jiangcheng Qin; Linze Luo (ISCC, 2023)

A split-federated learning and edge-cloud based efficient and privacy-preserving large-scale item recommendation model. - Jiangcheng Qin; Xueyuan Zhang; Baisong Liu; Jiangbo Qian (J. Cloud Comput., 2023)

Sequential POI Recommend Based on Personalized Federated Learning. - Qian Dong; Baisong Liu; Xueyuan Zhang; Jiangcheng Qin; Bingyuan Wang (Neural Process. Lett., 2023)

Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation. - Jiangcheng Qin; Xueyuan Zhang; Baisong Liu; Jiangbo Qian; Yangyang Wang (CoRR, 2025)