Experiments on Neighborhood Combination Strategies for Bi-objective Unconstrained Binary Quadratic Programming Problem. - Li-Yuan Xue; Rong-Qiang Zeng; Wei An; Qing-Xian Wang 001; Mingsheng Shang 001 (PAAP, 2017)

Incremental Slope-one recommenders. - Qing-Xian Wang 001; Xin Luo 001; Yan Li; Xiaoyu Shi 001; Liang Gu; Mingsheng Shang 001 (Neurocomputing, 2018)

DCCR: Deep Collaborative Conjunctive Recommender for Rating Prediction. - Qingxian Wang 001; Binbin Peng; Xiaoyu Shi 001; Tianqi Shang; Mingsheng Shang 001 (IEEE Access, 2019)

An adaptive latent factor model via particle swarm optimization. - Qingxian Wang 001; Sili Chen; Xin Luo 001 (Neurocomputing, 2019)

A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction. - Qingxian Wang 001; Minzhi Chen; Mingsheng Shang 001; Xin Luo 001 (Neurocomputing, 2019)

A Non-Negative Matrix-Factorization-Based Network Embedding Approach for Hybrid Recommender Systems. - Qingxian Wang 001; Mei Long; Han Yang (CNIOT, 2020)

Siamese Generative Adversarial Predicting Network for Extremely Sparse Data in Recommendation System. - Qingxian Wang 001; Renjian Zhang; Kangkang Ma; Bo Chen; Jiufang Chen; Xiaoyu Shi 001 (ISPA/BDCloud/SocialCom/SustainCom, 2021)

Joint Modeling Dynamic Preferences of Users and Items Using Reviews for Sequential Recommendation. - Tianqi Shang; Xinxin Li; Xiaoyu Shi 001; Qingxian Wang 001 (PAKDD (2), 2021)

A Recommender System Based on Model Regularization Wasserstein Generative Adversarial Network. - Qingxian Wang 001; Qing Huang; Kangkang Ma; Xuerui Zhang (SMC, 2021)

Inference and Prediction in Big Data Using Sparse Gaussian Process Method. - Leta Yobsan Bayisa; Weidong Wang; Qing-Xian Wang 001; Gurmu Meseret Debele; Lamessa Bona Debela (ICDSP, 2022)

Multi-Constrained Embedding for Accurate Community Detection on Undirected Networks. - Qingxian Wang 001; Xinyu Liu 022; Tianqi Shang; Zhigang Liu 006; Han Yang; Xin Luo 001 (IEEE Trans. Netw. Sci. Eng., 2022)

Neighbor importance-aware graph collaborative filtering for item recommendation. - Qingxian Wang 001; Suqiang Wu; Yanan Bai; Quanliang Liu; Xiaoyu Shi 001 (Neurocomputing, 2023)