Researches on Integrating Database Access Control and Privacy Protection. - Yonghong Yu (IAS, 2009)

Forecasting Model over Random Interval Data Stream Based on Kalman Filter. - Yonghong Yu; Wenyang Bai (DBTA, 2009)

The Design of the Automatic Control System of the Gripping-Belt Speed in Long-Rootstalk Traditional Chinese Herbal Harvester. - Jinxia Huang; Junfa Wang; Yonghong Yu (CCTA, 2009)

Enforcing Data Privacy and User Privacy over Outsourced Database Service. - Yonghong Yu; Wenyang Bai (J. Softw., 2011)

Constraint Programming-Based Virtual Machines Placement Algorithm in Datacenter. - Yonghong Yu; Yang Gao 001 (IIP, 2012)

A Coupled Clustering Approach for Items Recommendation. - Yonghong Yu; Can Wang 004; Yang Gao 001; Longbing Cao; Xixi Chen (PAKDD (2), 2013)

Erratum: A Coupled Clustering Approach for Items Recommendation. - Yonghong Yu; Can Wang 004; Yang Gao 001; Longbing Cao; Qianqian Chen (PAKDD (2), 2013)

Attributes Coupling based Item Enhanced Matrix Factorization Technique for Recommender Systems. - Yonghong Yu; Can Wang 004; Yang Gao 001 (CoRR, 2014)

Exploiting Location Significance and User Authority for Point-of-Interest Recommendation. - Yonghong Yu; Hao Wang 013; Shuanzhu Sun; Yang Gao 001 (PAKDD (2), 2017)

Attributes coupling based matrix factorization for item recommendation. - Yonghong Yu; Can Wang 004; Hao Wang 013; Yang Gao 001 (Appl. Intell., 2017)

Geographical Proximity Boosted Recommendation Algorithms for Real Estate. - Yonghong Yu; Can Wang 004; Li Zhang 013; Rong Gao; Hua Wang 002 (WISE (2), 2018)

Joint user knowledge and matrix factorization for recommender systems. - Yonghong Yu; Yang Gao 001; Hao Wang 013; Ruili Wang (World Wide Web, 2018)

A Methodology for Resolving Heterogeneity and Interdependence in Data Analytics. - Han Han; Yunwei Zhao; Can Wang 004; Min Shu; Tao Peng; Chi-Hung Chi; Yonghong Yu (ADMA, 2019)

The LAIX Systems in the BEA-2019 GEC Shared Task. - Ruobing Li; Chuan Wang; Yefei Zha; Yonghong Yu; Shiman Guo; Qiang Wang; Yang Liu; Hui Lin (BEA@ACL, 2019)

Integrating Social Circles and Network Representation Learning for Item Recommendation. - Yonghong Yu; Qiang Wang; Li Zhang 013; Can Wang 004; Sifan Wu; Boyu Qi; Xiaotian Wu (IJCNN, 2019)

Evolving Ensemble Models for Image Segmentation Using Enhanced Particle Swarm Optimization. - Teck Yan Tan; Li Zhang 013; Chee Peng Lim; Ben Fielding; Yonghong Yu; Emma Anderson (IEEE Access, 2019)

Network Representation Learning Enhanced Recommendation Algorithm. - Qiang Wang; Yonghong Yu; Haiyan Gao; Li Zhang 013; Yang Cao; Lin Mao; Kaiqi Dou; Wenye Ni (IEEE Access, 2019)

SSSER: Spatiotemporal Sequential and Social Embedding Rank for Successive Point-of-Interest Recommendation. - Yangyang Xu; Xuefei Li 001; Jing Li 055; Chunzhi Wang; Rong Gao; Yonghong Yu (IEEE Access, 2019)

Improving K-means clustering with enhanced Firefly Algorithms. - Hailun Xie; Li Zhang 013; Chee Peng Lim; Yonghong Yu; Chengyu Liu 001; Han Liu 002; Julie Walters (Appl. Soft Comput., 2019)

Neural Personalized Ranking via Poisson Factor Model for Item Recommendation. - Yonghong Yu; Li Zhang 013; Can Wang 004; Rong Gao; Weibin Zhao; Jing Jiang 019 (Complex., 2019)

Neural Pairwise Ranking Factorization Machine for Item Recommendation. - Lihong Jiao; Yonghong Yu; Ningning Zhou; Li Zhang 013; Hongzhi Yin (DASFAA (1), 2020)

Graph Neural Networks Boosted Personalized Tag Recommendation Algorithm. - Xuewen Chen; Yonghong Yu; Fengyixin Jiang; Li Zhang 013; Rong Gao; Haiyan Gao (IJCNN, 2020)

TRec: Sequential Recommender Based On Latent Item Trend Information. - Ye Tao 004; Can Wang 004; Lina Yao 001; Weimin Li 001; Yonghong Yu (IJCNN, 2020)

HHA: An Attentive Prediction Model for Academic Abnormality. - Yawen Zeng; Yong Ouyang; Rong Gao; Ye Qiu; Yonghong Yu; Chunzhi Wang (IEEE Access, 2020)

Elective future: The influence factor mining of students' graduation development based on hierarchical attention neural network model with graph. - Yong Ouyang; Yawen Zeng; Rong Gao; Yonghong Yu; Chunzhi Wang (Appl. Intell., 2020)

Enhanced factorization machine via neural pairwise ranking and attention networks. - Yonghong Yu; Lihong Jiao; Ningning Zhou; Li Zhang 013; Hongzhi Yin (Pattern Recognit. Lett., 2020)

Deep Recurrent Neural Networks with Attention Mechanisms for Respiratory Anomaly Classification. - Conor Wall; Li Zhang 013; Yonghong Yu; Kamlesh Mistry (IJCNN, 2021)

Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization. - Li Zhang 013; Chee Peng Lim; Yonghong Yu (Knowl. Based Syst., 2021)

Feature Selection Using Enhanced Particle Swarm Optimisation for Classification Models. - Hailun Xie; Li Zhang 013; Chee Peng Lim; Yonghong Yu; Han Liu 002 (Sensors, 2021)

Hyperbolic Personalized Tag Recommendation. - Weibin Zhao; Aoran Zhang 001; Lin Shang 001; Yonghong Yu; Li Zhang 013; Can Wang 004; Jiajun Chen 001; Hongzhi Yin (DASFAA (2), 2022)

Human Action Recognition Using Hybrid Deep Evolving Neural Networks. - Pavan Dasari; Li Zhang 013; Yonghong Yu; Haoqian Huang; Rong Gao (IJCNN, 2022)

Gated Dual Hypergraph Convolutional Networks for Recommendation with Self-supervised Learning. - Rong Gao; Jiakang Liu; Yonghong Yu; Donghua Liu; Xiongkai Shao; Zhiwei Ye (IJCNN, 2022)

Sound classification using evolving ensemble models and Particle Swarm Optimization. - Li Zhang 013; Chee Peng Lim; Yonghong Yu; Ming Jiang 020 (Appl. Soft Comput., 2022)

Neural Graph for Personalized Tag Recommendation. - Yonghong Yu; Xuewen Chen; Li Zhang 013; Rong Gao; Haiyan Gao (IEEE Intell. Syst., 2022)

An evolving ensemble model of multi-stream convolutional neural networks for human action recognition in still images. - Sam Slade; Li Zhang 013; Yonghong Yu; Chee Peng Lim (Neural Comput. Appl., 2022)

A Deep Ensemble Neural Network with Attention Mechanisms for Lung Abnormality Classification Using Audio Inputs. - Conor Wall; Li Zhang 013; Yonghong Yu; Akshi Kumar 001; Rong Gao (Sensors, 2022)

A Faster and More Accurate Iterative Threshold Algorithm for Signal Reconstruction in Compressed Sensing. - Jianxiang Wei; Shumin Mao; Jiming Dai; Ziren Wang; Weidong Huang 007; Yonghong Yu (Sensors, 2022)

A Graph-Neural-Network-Based Social Network Recommendation Algorithm Using High-Order Neighbor Information. - Yonghong Yu; Weiwen Qian; Li Zhang 013; Rong Gao (Sensors, 2022)

Self-supervised Dual Hypergraph learning with Intent Disentanglement for session-based recommendation. - Rong Gao; Yuhe Tao; Yonghong Yu; Jia Wu 001; Xiongkai Shao; Jing Li 055; Zhiwei Ye (Knowl. Based Syst., 2023)

High-order deep infomax-guided deformable transformer network for efficient lane detection. - Rong Gao; Siqi Hu; Lingyu Yan; Li Zhang; Hang Ruan; Yonghong Yu; Zhiwei Ye (Signal Image Video Process., 2023)

Personalized tag recommendation via denoising auto-encoder. - Weibin Zhao; Lin Shang 001; Yonghong Yu; Li Zhang 013; Can Wang 004; Jiajun Chen 001 (World Wide Web (WWW), 2023)

Item trend learning for sequential recommendation system using gated graph neural network. - Ye Tao 004; Can Wang 004; Lina Yao 001; Weimin Li 001; Yonghong Yu (Neural Comput. Appl., 2023)

Hyperbolic Adversarial Learning for Personalized Item Recommendation. - Aoran Zhang 001; Yonghong Yu; Gongyou Xu; Rong Gao; Li Zhang 013; Shang Gao; Hongzhi Yin (DASFAA (3), 2024)

A Graph Neural Networks-Based Learning Framework With Hyperbolic Embedding for Personalized Tag Recommendation. - Chunmei Zhang; Aoran Zhang 001; Li Zhang 013; Yonghong Yu; Weibin Zhao; Hai Geng (IEEE Access, 2024)

Video Deepfake classification using particle swarm optimization-based evolving ensemble models. - Li Zhang 013; Dezong Zhao; Chee Peng Lim; Houshyar Asadi; Haoqian Huang; Yonghong Yu; Rong Gao (Knowl. Based Syst., 2024)

Hybrid graph transformer networks for multivariate time series anomaly detection. - Rong Gao; Wei He; Lingyu Yan; Donghua Liu; Yonghong Yu; Zhiwei Ye (J. Supercomput., 2024)

Contrastive graph learning long and short-term interests for POI recommendation. - Jiarun Fu; Rong Gao; Yonghong Yu; Jia Wu 001; Jing Li 055; Donghua Liu; Zhiwei Ye (Expert Syst. Appl., 2024)

Contrastive Learning-Based Personalized Tag Recommendation. - Aoran Zhang 001; Yonghong Yu; Shenglong Li; Rong Gao; Li Zhang 013; Shang Gao (Sensors, 2024)

Neural Inference Search for Multiloss Segmentation Models. - Sam Slade; Li Zhang 013; Haoqian Huang; Houshyar Asadi; Chee Peng Lim; Yonghong Yu; Dezong Zhao; Hanhe Lin; Rong Gao (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hyperbolic Translation-Based Sequential Recommendation. - Yonghong Yu; Aoran Zhang 001; Li Zhang 013; Rong Gao; Shang Gao; Hongzhi Yin (IEEE Trans. Comput. Soc. Syst., 2024)

PDC & DM-SFT: A Road for LLM SQL Bug-Fix Enhancing. - Yiwen Duan; Yonghong Yu; Xiaoming Zhao; Yichang Wu; Wenbo Liu (COLING (Industry), 2025)

Cluster search optimisation of deep neural networks for audio emotion classification. - Sam Slade; Li Zhang 013; Houshyar Asadi; Chee Peng Lim; Yonghong Yu; Dezong Zhao; Arjun Panesar; Philip Fei Wu; Rong Gao (Knowl. Based Syst., 2025)

Dynamic deep graph convolution with enhanced transformer networks for time series anomaly detection in IoT. - Rong Gao; Zhiwei Chen; Xinyun Wu; Yonghong Yu; Li Zhang (Clust. Comput., 2025)

Contrastive Translation With Dynamical Temperature for Sequential Recommendation. - Aoran Zhang 001; Yonghong Yu; Li Zhang 013; Rong Gao; Hongzhi Yin (IEEE Trans. Syst. Man Cybern. Syst., 2025)