Mining the Semantic Information to Facilitate Reading Comprehension. - Yongping Du; Ming He 001; Naiwen Ye (ICIC (1), 2007)

Multi-Strategy to Improve Reading Comprehension. - Yongping Du; Ming He 001 (CIS (1), 2008)

Pattern Optimization and the Application in Question Answering. - Yongping Du; Ming He 001 (ISDA (2), 2008)

P-top-k queries in probabilistic framework from information extraction models. - Ming He 001; Yongping Du (FSKD, 2010)

Uncertain Queries Processing in Probabilistic Framework. - Ming He 001; Yongping Du (J. Comput., 2010)

p-top-k queries in a probabilistic framework from information extraction models. - Ming He 001; Yongping Du (Comput. Math. Appl., 2011)

Robust Transfer Learning for Cross-domain Collaborative Filtering Using Multiple Rating Patterns Approximation. - Ming He 001; Jiuling Zhang; Peng Yang; Kaisheng Yao (WSDM, 2018)

基于标签信息特征相似性的协同过滤个性化推荐 (Collaborative Filtering Personalized Recommendation Based on Similarity of Tag Information Feature). - Ming He 001; Kaisheng Yao; Peng Yang; Jiuling Zhang (计算机科学, 2018)

TEFRCF: 标签熵特征表示的协同过滤个性化推荐算法 (TEFRCF: Collaborative Filtering Personalized Recommendation Algorithm Based on TagEntropy Feature Representation). - Ming He 001; Peng Yang; Kaisheng Yao; Jiuling Zhang (计算机科学, 2018)

Tag2Vec: Tag Embedding for Top-N Recommendation. - Ming He 001; Kaisheng Yao; Peng Yang; Yuan Yao (ICNC-FSKD, 2019)

Representation Learning of Knowledge Graphs via Fine-Grained Relation Description Combinations. - Ming He 001; Xiangkun Du; Bo Wang 037 (IEEE Access, 2019)

Collaborative Additional Variational Autoencoder for Top-N Recommender Systems. - Ming He 001; Qian Meng; Shaozong Zhang (IEEE Access, 2019)

HI2Rec: Exploring Knowledge in Heterogeneous Information for Movie Recommendation. - Ming He 001; Bo Wang 037; Xiangkun Du (IEEE Access, 2019)

Learning to Style-Aware Bayesian Personalized Ranking for Visual Recommendation. - Ming He 001; Shaozong Zhang; Qian Meng (IEEE Access, 2019)

ACTL: Adaptive Codebook Transfer Learning for Cross-Domain Recommendation. - Ming He 001; Jiuling Zhang; Shaozong Zhang (IEEE Access, 2019)

Restoring latent factors against negative transfer using partial-adaptation nonnegative matrix factorization. - Ming He 001; Jiuling Zhang; Jiang Zhang (CCF Trans. Pervasive Comput. Interact., 2020)

LGCCF: A Linear Graph Convolutional Collaborative Filtering with Social Influence. - Ming He 001; Han Wen; Hanyu Zhang (DASFAA (3), 2021)

RE-KGR: Relation-Enhanced Knowledge Graph Reasoning for Recommendation. - Ming He 001; Hanyu Zhang; Han Wen (DASFAA (3), 2021)

MPIA: Multiple Preferences with Item Attributes for Graph Convolutional Collaborative Filtering. - Ming He 001; Zekun Huang; Han Wen (ICWE, 2021)

Conversation and Recommendation: Knowledge-Enhanced Personalized Dialog System. - Ming He 001; Tong Shen; Ruihai Dong (ICWE, 2021)

SAGCN: Towards Structure-Aware Deep Graph Convolutional Networks on Node Classification. - Ming He 001; Tianyu Ding; Tianshuo Han (PAKDD (2), 2021)

CRTL: Context Restoration Transfer Learning for Cross-Domain Recommendations. - Jiuling Zhang; Ming He 001 (IEEE Intell. Syst., 2021)

Causal Intervention for Sentiment De-biasing in Recommendation. - Ming He 001; Xin Chen; Xinlei Hu; Changshu Li (CIKM, 2022)

Learning and Fusing Multiple User Interest Representations for Sequential Recommendation. - Ming He 001; Tianshuo Han; Tianyu Ding (DASFAA (3), 2022)

Mitigating Popularity Bias in Recommendation via Counterfactual Inference. - Ming He 001; Changshu Li; Xinlei Hu; Xin Chen; Jiwen Wang (DASFAA (3), 2022)

Multilevel Feature Interaction Learning for Session-Based Recommendation via Graph Neural Networks. - Ming He 001; Tianshuo Han; Tianyu Ding (ICWE, 2022)

Mitigating Confounding Bias for Recommendation via Counterfactual Inference. - Ming He 001; Xinlei Hu; Changshu Li; Xin Chen; Jiwen Wang (ECML/PKDD (1), 2022)

Conversation and recommendation: knowledge-enhanced personalized dialog system. - Ming He 001; Jiwen Wang; Tianyu Ding; Tong Shen (Knowl. Inf. Syst., 2023)

Causal Disentangled Sentiment Debiasing for Recommendation. - Ming He 001; Chang Liu; Han Zhang; Zihao Zhang (DASFAA (3), 2024)

Relieving popularity bias in recommender systems via user group-level augmentation. - Ming He 001; Zihao Zhang; Han Zhang; Chang Liu (Appl. Soft Comput., 2025)

DTR4Rec: direct transition relationship for sequential recommendation. - Ming He 001; Han Zhang; Zihao Zhang; Chang Liu (Appl. Intell., 2025)