Preference Integration in Context-Aware Recommendation. - Lin Zheng 003; Fuxi Zhu (DASFAA (1), 2017)

Attribute and Global Boosting: A Rating Prediction Method in Context-Aware Recommendation. - Lin Zheng 003; Fuxi Zhu; Alshahrani Mohammed (Comput. J., 2017)

Context Neighbor Recommender: Integrating contexts via neighbors for recommendations. - Lin Zheng 003; Fuxi Zhu; Sheng Huang; Jin Xie (Inf. Sci., 2017)

Sentiment-guided Sequential Recommendation. - Lin Zheng 003; Naicheng Guo; Weihao Chen; Jin Yu; Dazhi Jiang (SIGIR, 2020)

Factorization Meets Neural Networks: A Scalable and Efficient Recommender for Solving the New User Problem. - Dazhi Jiang; Zhichao Liu; Lin Zheng 003; Jianwei Chen (IEEE Access, 2020)

Memory Reorganization: A Symmetric Memory Network for Reorganizing Neighbors and Topics to Complete Rating Prediction. - Lin Zheng 003; Naicheng Guo; Jin Yu; Dazhi Jiang (IEEE Access, 2020)

A Multitask Learning Framework for Multimodal Sentiment Analysis. - Dazhi Jiang; Runguo Wei; Hao Liu; Jintao Wen; Geng Tu; Lin Zheng 003; Erik Cambria (ICDM (Workshops), 2021)

HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation. - Naicheng Guo; Xiaolei Liu; Shaoshuai Li; Qiongxu Ma; Yunan Zhao; Bing Han 017; Lin Zheng 003; Kai-Xin Gao; Xiaobo Guo (CoRR, 2021)

Differences first in asymmetric brain: A bi-hemisphere discrepancy convolutional neural network for EEG emotion recognition. - Dongmin Huang; Sentao Chen; Cheng Liu 001; Lin Zheng 003; Zhihang Tian; Dazhi Jiang (Neurocomputing, 2021)

Multimodality Sentiment Analysis in Social Internet of Things Based on Hierarchical Attentions and CSAT-TCN With MBM Network. - Guorong Xiao; Geng Tu; Lin Zheng 003; Teng Zhou; Xin Li 102; Syed Hassan Ahmed; Dazhi Jiang (IEEE Internet Things J., 2021)

A hybrid intelligent model for acute hypotensive episode prediction with large-scale data. - Dazhi Jiang; Geng Tu; Donghui Jin; Kaichao Wu; Cheng Liu 001; Lin Zheng 003; Teng Zhou (Inf. Sci., 2021)

Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation. - Naicheng Guo; Xiaolei Liu; Shaoshuai Li; Qiongxu Ma; Kai-Xin Gao; Bing Han 017; Lin Zheng 003; Xiaobo Guo (CoRR, 2022)

Exploration meets exploitation: Multitask learning for emotion recognition based on discrete and dimensional models. - Geng Tu; Jintao Wen; Hao Liu 080; Sentao Chen; Lin Zheng 003; Dazhi Jiang (Knowl. Based Syst., 2022)

Poincaré Heterogeneous Graph Neural Networks for Sequential Recommendation. - Naicheng Guo; Xiaolei Liu; Shaoshuai Li; Qiongxu Ma; Kaixin Gao; Bing Han 017; Lin Zheng 003; Sheng Guo 005; Xiaobo Guo (ACM Trans. Inf. Syst., 2023)

Riemannian representation learning for multi-source domain adaptation. - Sentao Chen; Lin Zheng 003; Hanrui Wu (Pattern Recognit., 2023)

User view dynamic graph-driven sequential recommendation. - Jianzhen Chen; Lin Zheng 003; Sentao Chen (Knowl. Inf. Syst., 2023)

Maximum likelihood weight estimation for partial domain adaptation. - Lisheng Wen; Sentao Chen; Zijie Hong; Lin Zheng 003 (Inf. Sci., 2024)

Training multi-source domain adaptation network by mutual information estimation and minimization. - Lisheng Wen; Sentao Chen; Mengying Xie; Cheng Liu 001; Lin Zheng 003 (Neural Networks, 2024)

Adaptive dual graph regularization for clustered multi-task learning. - Cheng Liu 001; Rui Li 045; Sentao Chen; Lin Zheng 003; Dazhi Jiang (Neurocomputing, 2024)

Recurrent-optimized user association representation for multi-target cross-domain sequential recommendation. - Nuo Chen; Lin Zheng 003; Sentao Chen (Knowl. Inf. Syst., 2025)