A Random Forest Regression-based Personalized Recommendation Method. - Yingxue Ma; Mingxin Gan (PACIS, 2018)

CDMF: A Deep Learning Model based on Convolutional and Dense-layer Matrix Factorization for Context-Aware Recommendation. - Mingxin Gan; Yingxue Ma; Kejun Xiao (HICSS, 2019)

Gradient Boosting Based Prediction Method for Patient Death in Hospital Treatment. - Yingxue Ma; Mingxin Gan (ICSH, 2019)

Exploring multiple spatio-temporal information for point-of-interest recommendation. - Yingxue Ma; Mingxin Gan (Soft Comput., 2020)

DeepAssociate: A deep learning model exploring sequential influence and history-candidate association for sequence recommendation. - Yingxue Ma; Mingxin Gan (Expert Syst. Appl., 2021)

Exploring the Influencing Factors of IP Film Rating by Sentiment Analysis and GMM. - Yingxue Ma; Mingxin Gan; Jiao Xv (HICSS, 2022)

DeepInteract: Multi-view features interactive learning for sequential recommendation. - Mingxin Gan; Yingxue Ma (Expert Syst. Appl., 2022)

Knowledge transfer learning from multiple user activities to improve personalized recommendation. - Mingxin Gan; Yingxue Ma (Soft Comput., 2022)

Mapping user interest into hyper-spherical space: A novel POI recommendation method. - Mingxin Gan; Yingxue Ma (Inf. Process. Manag., 2023)

A multi-behavior recommendation method exploring the preference differences among various behaviors. - Mingxin Gan; Gangxin Xu; Yingxue Ma (Expert Syst. Appl., 2023)

Optimization Strategy for MAPF Problem with Traffic Rule-based CBS Algorithm in Warehouses. - Yang Wang 138; Shaoyun Xu; Yingxue Ma; Yuexing Hao; Yanbo Qu; Yuhui Sun; Shu Zhang (CIIS, 2024)

Sequential-hierarchical attention network: Exploring the hierarchical intention feature in POI recommendation. - Yingxue Ma; Mingxin Gan (World Wide Web (WWW), 2024)