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FedCDR: Federated Cross-Domain Recommendation for Privacy-Preserving Rating Prediction Conference paper
Meihan Wu, Li Li, Tao Chang, Eric Rigall, Xiaodong Wang, ChengZhong Xu. FedCDR: Federated Cross-Domain Recommendation for Privacy-Preserving Rating Prediction[C]. Mohammad Al Hasan, Li Xiong, New York, NY, United States:Association for Computing Machinery, 2022, 2179–2188.
Authors:  Meihan Wu;  Li Li;  Tao Chang;  Eric Rigall;  Xiaodong Wang; et al.
Favorite | TC[WOS]:11 TC[Scopus]:19 | Submit date：2022/08/30
Personalized Federated Learning  Cross-domain Recommendation  Cold-start Problem  Rating Prediction  
Multi-Task Learning with Personalized Transformer for Review Recommendation Conference paper
Haiming Wang, Wei Liu, Jian Yin. Multi-Task Learning with Personalized Transformer for Review Recommendation[C]:Springer, Cham, 2021, 162-176.
Authors:  Haiming Wang;  Wei Liu;  Jian Yin
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2022/05/13
Multi-task Learning  Personalized Transformer  Review Recommendation  
Personalized Re-ranking with Item Relationships for E-commerce Conference paper
Liu, Weiwen, Liu, Qing, Tang, Ruiming, Chen, Junyang, He, Xiuqiang, Heng, Pheng Ann. Personalized Re-ranking with Item Relationships for E-commerce[C], 2020, 925-934.
Authors:  Liu, Weiwen;  Liu, Qing;  Tang, Ruiming;  Chen, Junyang;  He, Xiuqiang; et al.
Favorite | TC[WOS]:18 TC[Scopus]:28 | Submit date：2021/12/06
Graph Neural Networks  Item Relationships  Personalized Re-ranking  Recommendation  
Knowledge Modeling via Contextualized Representations for LSTM-based Personalized Exercise Recommendation Journal article
Huo, Y., Wong, F., Chao, S., Ni, M., Zhang, J.. Knowledge Modeling via Contextualized Representations for LSTM-based Personalized Exercise Recommendation[J]. Information Sciences, 2020, 266-278.
Authors:  Huo, Y.;  Wong, F.;  Chao, S.;  Ni, M.;  Zhang, J.
Favorite |   IF:0/0 | Submit date：2022/08/08
Personalized learning  Knowledge tracing  LSTM  Context representation  Exercise recommendation  
Knowledge modeling via contextualized representations for LSTM-based personalized exercise recommendation Journal article
Huo,Yujia, Wong,Derek F., Ni,Lionel M., Chao,Lidia S., Zhang,Jing. Knowledge modeling via contextualized representations for LSTM-based personalized exercise recommendation[J]. INFORMATION SCIENCES, 2020, 523, 266-278.
Authors:  Huo,Yujia;  Wong,Derek F.;  Ni,Lionel M.;  Chao,Lidia S.;  Zhang,Jing
Favorite | TC[WOS]:46 TC[Scopus]:71  IF:0/0 | Submit date：2021/03/11
Context Representation  Exercise Recommendation  Knowledge Tracing  Lstm  Personalized Learning  
Towards Personalized Learning Through Class Contextual Factors-Based Exercise Recommendation Conference paper
Huo, Yujia, Xiao, Jiang, Ni, Lionel M.. Towards Personalized Learning Through Class Contextual Factors-Based Exercise Recommendation[C], 2019, 85-92.
Authors:  Huo, Yujia;  Xiao, Jiang;  Ni, Lionel M.
Favorite | TC[WOS]:9 TC[Scopus]:12 | Submit date：2022/04/15
Attribute-based Recommendation  Learning Remediation  Performance Prediction  Personalized Learning  Q-matrix  Recommender Systems  
A novel item anomaly detection approach against shilling attacks in collaborative recommendation systems using the dynamic time interval segmentation technique Journal article
Xia H., Fang B., Gao M., Ma H., Tang Y., Wen J.. A novel item anomaly detection approach against shilling attacks in collaborative recommendation systems using the dynamic time interval segmentation technique[J]. Information Sciences, 2015, 306, 150-165.
Authors:  Xia H.;  Fang B.;  Gao M.;  Ma H.;  Tang Y.; et al.
Favorite | TC[WOS]:47 TC[Scopus]:60 | Submit date：2019/02/11
Anomaly Detection  Personalized Recommendation  Skewness  Stability  Time Interval