Publications By Topics

Xurong Liang, Tong Chen, Lizhen Cui, Yang Wang, Meng Wang and Hongzhi Yin*. "Lightweight Embeddings for Graph Collaborative Filtering". The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'24), July 14-18, 2024, Washington D.C., USA.

Hongzhi Yin, Tong Chen, Liang Qu, Bin Cui. "On-Device Recommender Systems: A Tutorial on The New-Generation Recommendation Paradigm". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Ruiqi Zheng, Liang Qu, Tong Chen, Kai Zheng, Yuhui Shi, Hongzhi Yin*. "Personalized Elastic Embedding Learning for On-Device Recommendation".  Accepted by IEEE Transactions on Knowledge and Data Engineering. 2024. (TKDE'24). (CCF Rank A, CORE Rank A*, Q1 Journal)

Yunke Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Budgeted Embedding Table For Recommender Systems". The 17th ACM International Conference on Web Search and Data Mining (WSDM'24), March 4-8, 2024, Mérida, México. (CORE Rank A, CCF Rank B, Tsinghua Rank A; Corresponding Author)

Xurong Liang, Tong Chen, Quoc Viet Hung Nguyen, Jianxin Li, Hongzhi Yin*. "Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation". IEEE International Conference on Data Mining 2023 (ICDM'23),  December 1-4, 2023, Shanghai, China.  (CCF Rank B, CORE Rank A*; Corresponding Author)

Xin Xia, Junliang Yu, Guandong Xu and Hongzhi Yin*. "Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation". The 32nd ACM International Conference on Information and Knowledge Management  (CIKM'23), 21-25 October 2023, Birmingham, UK. (CCF Rank B, CORE Rank A; Corresponding Author)

Yunke Qu, Tong Chen, Xiangyu Zhao, Lizhen Cui, Kai Zheng, Hongzhi Yin*. "Continuous Input Embedding Size Search For Recommender Systems". The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23), Taipei,  23-27 July, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Yuting Sun, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin*. "TinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT" .  IEEE Transactions on Industrial Informatics (TII) 2023. (Corresponding author; CORE Rank A*, Q1 Journal)

Xin Xia, Junliang Yu, Qinyong Wang, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin*.  "Efficient On-Device Session-Based Recommendation". ACM Transactions on Information Systems. 2023. (TOIS'23). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Junliang Yu, Xin Xia, Tong Chen, Lizhen Cui, Nguyen Quoc Viet Hung, Hongzhi Yin*. "XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)

Junliang Yu, Hongzhi Yin*, Xin Xia, Tong Chen, Lizhen Cui and Quoc Viet Hung Nguyen . "Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation". The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'22), July, 2022. (CCF Rank A, CORE Rank A*; Corresponding author).

Junliang Yu, Xin Xia, Tong Chen, Lizhen Cui, Nguyen Quoc Viet Hung, Hongzhi Yin*. "XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation". https://arxiv.org/abs/2209.02544

Xin Xia, Hongzhi Yin*, Junliang Yu, Qinyong Wang, Guandong Xu and Quoc Viet Hung Nguyen . "On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation". The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'22), July, 2022. (CCF Rank A, CORE Rank A*; Corresponding author). 

Tong Chen, Hongzhi Yin*, Yujia Zheng, Zi Huang, Yang Wang, Meng Wang. "Learning Elastic Embeddings for Customizing On-Device Recommenders". The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'21), Singapore. August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Guanhua Ye, Hongzhi Yin*, Tong Chen, Hongxu Chen, Lizhen Cui, Xiangliang Zhang. "FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection".IEEE Journal of Biomedical and Health Informatics, 2021. (JBHI'21). (Corresponding author, Q1 Journal, CORE Rank A*)

Tong Chen, Hongzhi Yin*, Xiangliang Zhang, Zi Huang, Yang Wang, Meng Wang. "Quaternion Factorization Machines: A Lightweight Solution to Intricate Feature Interaction Modelling" . IEEE Transactions on Neural Networks and Learning Systems (TNNLs), 2021. (Corresponding author; CORE Rank A*, Q1 Journal) 

Yang Li, Tong Chen, Pengfei Zhang, Hongzhi Yin. "Lightweight Self-Attentive Sequential Recommendation ".  The 30th ACM International Conference on Information and Knowledge Management (CIKM'21), October, 2021. (CCF Rank B, CORE Rank A).

Pengfei Zhang, Jiasheng Duan, Zi Huang, Hongzhi Yin. "Joint-teaching: Learning to Refine Knowledge for Resource-constrained Unsupervised Cross-modal Retrieval". The 29th ACM International Conference on Multimedia (MM'21), 2021.  (CCF Rank A, CORE Rank A*)

Qinyong Wang, Hongzhi Yin*, Tong Chen, Zi Huang, Hao Wang, Yanchang Zhao, Quoc Viet Hung Nguyen. "Next Point-of-Interest Recommendation on Resource-Constrained Mobile Devices". The Web Conference 2020 (WWW'2020), Taipei, Taiwan. April, 2020. (CCF Rank A, CORE Rank A*, Acceptance Rate 19% , Corresponding author and supervisor of the first author; Contributing equally with the first author).

Yan Zhang, Ivor W. Tsang, Hongzhi Yin*, Guowu Yang, Defu Lian, Jingjing Li. "Deep Pairwise Hashing for Cold-start Recommendation". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (Corresponding author, CCF Rank A, CORE Rank A*)

Yan Zhang, Haoyu Wang, Defu Lian, Ivor W. Tsang, Hongzhi Yin, Guowu Yang. "Discrete Ranking-based Matrix Factorization with Self-Paced Learning". 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), London, United Kingdom. August, 2018. (CCF Rank A, CORE Rank A*. ).

Yan Zhang, Hongzhi Yin*, Zi Huang, Xingzhong Du, Guowu Yang and Diefu Lian. "Discrete Deep Learning for Fast Content-Aware Recommendation". Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining (WSDM'18), Marina Del Rey, CA, USA, 2018. (CCF Rank B, CORE Rank A*, Slides Download, Codes Download).

Jing Long, Guanhua Ye,  Tong Chen, Yang Wang, Meng Wang, Hongzhi Yin*. "Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations". The 30th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'24), 25-29 August, 2024, Barcelona, Spain. (CCF Rank A, CORE Rank A*; Corresponding Author).

Ruiqi Zheng, Liang Qu, Tong Chen, Kai Zheng, Yuhui Shi and Hongzhi Yin*. "Poisoning Decentralized Collaborative Recommender System and Its Countermeasures". The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'24), July 14-18, 2024, Washington D.C., USA.

Hongzhi Yin, Tong Chen, Liang Qu, Bin Cui. "On-Device Recommender Systems: A Tutorial on The New-Generation Recommendation Paradigm". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Wei Yuan, Chaoqun Yang, Liang Qu, Quoc Viet Hung Nguyen, Jianxin Li, Hongzhi Yin*.  "Hide Your Model: A Parameter Transmission-free Federated Recommender System". The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Liang Qu, Wei Yuan, Ruiqi Zheng, Lizhen Cui, Yuhui Shi, Hongzhi Yin*. "Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Ruiqi Zheng, Liang Qu, Tong Chen, Lizhen Cui, Yuhui Shi, Hongzhi Yin*. "Decentralized Collaborative Learning with Adaptive Reference Data for On-Device POI Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Jing Long, Tong Chen, Guanhua Ye, Kai Zheng, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Physical Trajectory Inference Attack and Defense in Decentralized POI Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Lei Guo, Ziang Lu, Junliang Yu, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Prompt-enhanced Federated Content Representation Learning for Cross-domain Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Wei Yuan, Liang Qu, Lizhen Cui, Yongxin Tong, Xiaofang Zhou, Hongzhi Yin*. "HeteFedRec: Federated Recommender Systems with Model Heterogeneity". The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Wei Yuan, Shilong Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Manipulating Visually-aware Federated Recommender Systems and Its Countermeasures" . ACM Transactions on Information Systems. 2024. (TOIS'24). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Guanhua Ye, Tong Chen, Nguyen Quoc Viet Hung, Hongzhi Yin*. "Heterogeneous Decentralized Machine Unlearning with Seed Model Distillation".  Accepted by CAAI Transactions on Intelligence Technology. 2023. (Corresponding author, Q1 Journal)

Jing Long, Tong Chen, Nguyen Quoc Viet Hung, Guandong Xu, Kai Zheng, Hongzhi Yin*. "Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation". The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23), Taipei,  23-27 July, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Guanhua Ye, Tong Chen, Yawen Li, Lizhen Cui, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Heterogeneous Collaborative Learning for Personalized Healthcare Analytics via Messenger Distillation". IEEE Journal of Biomedical and Health Informatics (JBHI) 2023. (Corresponding author; CORE Rank A*, Q1 Journal)

Liang Qu, Ningzhi Tang, Ruiqi Zheng, Quoc Viet Hung Nguyen, Zi Huang, Yuhui Shi, Hongzhi Yin*. "Semi-decentralized Federated Ego Graph Learning for Recommendation" International World Wide Web Conference 2023 (WWW'23), AUSTIN, TEXAS, USA, APRIL 30 - MAY 4, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Lizhen Cui, Tieke He, Hongzhi Yin*. "Interaction-level Membership Inference Attack Against Federated Recommender Systems".  International World Wide Web Conference 2023 (WWW'23), AUSTIN, TEXAS, USA, APRIL 30 - MAY 4, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Wei Yuan, Hongzhi Yin*, Fangzhou Wu, Shijie Zhang, Tieke He, Hao Wang. "Federated Unlearning for On-Device Recommendation". The 16th ACM International WSDM Conference (WSDM'23), Singapore, February 27 to March 3, 2023. (CCF Rank B, CORE Rank A*, Corresponding author).

Jing Long, Tong Chen, Nguyen Quoc Viet Hung, Hongzhi Yin*.  "Decentralized Collaborative Learning Framework for Next POI Recommendation".  ACM Transactions on Information Systems. 2022. (TOIS'22). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Mubashir Imran, Hongzhi Yin*, Tong Chen, Nguyen Quoc Viet Hung, Alexander Zhou, Kai Zheng. "ReFRS: Resource-efficient Federated Recommender System for Dynamic and Diversified User Preferences".   ACM Transactions on Information Systems. 2022. (TOIS'22). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Shijie Zhang, Hongzhi Yin*,  Tong Chen, Zi Huang, Quoc Viet Hung Nguyen, Lizhen Cui. "PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion".  The 15th ACM International WSDM Conference (WSDM'22), March, 2022. (CCF Rank B, CORE Rank A*, Corresponding author).

Qinyong Wang,  Hongzhi Yin*, Tong Chen, Junliang Yu, Alexander Zhou and Xiangliang Zhang. "Fast-adapting and Privacy-preserving Federated Recommender System". The VLDB Journal 2021. (VLDBJ'21). (Corresponding author; CCF Rank A, CORE Rank A*, Q1 Journal)

Guanhua Ye, Hongzhi Yin*, Tong Chen, Miao Xu, Quoc Viet Hung Nguyen, Jiangning Song. "Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent". IEEE Journal of Biomedical and Health Informatics (JBHI) 2022. (Corresponding author; CORE Rank A*, Q1 Journal)

Ruiqi Zheng, Liang Qu, Tong Chen, Kai Zheng, Yuhui Shi and Hongzhi Yin*. "Poisoning Decentralized Collaborative Recommender System and Its Countermeasures". The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'24), July 14-18, 2024, Washington D.C., USA.

Hongzhi Yin, Tong Chen, Liang Qu, Bin Cui. "On-Device Recommender Systems: A Tutorial on The New-Generation Recommendation Paradigm". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Wei Yuan, Chaoqun Yang, Liang Qu, Quoc Viet Hung Nguyen, Jianxin Li, Hongzhi Yin*.  "Hide Your Model: A Parameter Transmission-free Federated Recommender System". The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Liang Qu, Wei Yuan, Ruiqi Zheng, Lizhen Cui, Yuhui Shi, Hongzhi Yin*. "Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Ruiqi Zheng, Liang Qu, Tong Chen, Lizhen Cui, Yuhui Shi, Hongzhi Yin*. "Decentralized Collaborative Learning with Adaptive Reference Data for On-Device POI Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Jing Long, Tong Chen, Guanhua Ye, Kai Zheng, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Physical Trajectory Inference Attack and Defense in Decentralized POI Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Wei Yuan, Shilong Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Manipulating Visually-aware Federated Recommender Systems and Its Countermeasures" . ACM Transactions on Information Systems. 2024. (TOIS'24). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Shijie Zhang, Wei Yuan, Hongzhi Yin*. "Comprehensive Privacy Analysis on Federated Recommender System against Attribute Inference Attacks". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)

Guanhua Ye, Tong Chen, Nguyen Quoc Viet Hung, Hongzhi Yin*. "Heterogeneous Decentralized Machine Unlearning with Seed Model Distillation".  Accepted by CAAI Transactions on Intelligence Technology. 2023. (Corresponding author, Q1 Journal)

Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, Hongzhi Yin*.  "Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures". The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23), Taipei,  23-27 July, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Lizhen Cui, Tieke He, Hongzhi Yin*. "Interaction-level Membership Inference Attack Against Federated Recommender Systems".  International World Wide Web Conference 2023 (WWW'23), AUSTIN, TEXAS, USA, APRIL 30 - MAY 4, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Wei Yuan, Hongzhi Yin*, Fangzhou Wu, Shijie Zhang, Tieke He, Hao Wang. "Federated Unlearning for On-Device Recommendation". The 16th ACM International WSDM Conference (WSDM'23), Singapore, February 27 to March 3, 2023. (CCF Rank B, CORE Rank A*, Corresponding author).

Shijie Zhang, Hongzhi Yin*,  Tong Chen, Zi Huang, Quoc Viet Hung Nguyen, Lizhen Cui. "PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion".  The 15th ACM International WSDM Conference (WSDM'22), March, 2022. (CCF Rank B, CORE Rank A*, Corresponding author).

Qinyong Wang,  Hongzhi Yin*, Tong Chen, Junliang Yu, Alexander Zhou and Xiangliang Zhang. "Fast-adapting and Privacy-preserving Federated Recommender System". The VLDB Journal 2021. (VLDBJ'21). (Corresponding author; CCF Rank A, CORE Rank A*, Q1 Journal)

Shijie Zhang, Hongzhi Yin*, Tong Chen, Zi Huang, Lizhen Cui and Xiangliang Zhang. "Graph Embedding for Recommendation against Attribute Inference Attacks". The Web Conference 2021 (WWW'21), April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Peng-Fei Zhang, Yang Li, Zi Huang and Hongzhi Yin. "Privacy Protection in Deep Multi-modal Retrieval". The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), July, 2021. (CCF Rank A, CORE Rank A*).

Pengfei Zhang, Guangdong Bai, Hongzhi Yin, Zi Huang. "Proactive Privacy-preserving Learning for Cross-modal Retrieval".  ACM Transactions on Information Systems. 2022. (TOIS'22). (CCF Rank A, CORE Rank A, Q1 Journal)

Yuting Sun, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin*. "TinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT" .  IEEE Transactions on Industrial Informatics (TII) 2023. (Corresponding author; CORE Rank A*, Q1 Journal)

Guanhua Ye, Tong Chen, Yawen Li, Lizhen Cui, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Heterogeneous Collaborative Learning for Personalized Healthcare Analytics via Messenger Distillation". IEEE Journal of Biomedical and Health Informatics (JBHI) 2023. (Corresponding author; CORE Rank A*, Q1 Journal)

Guanhua Ye, Hongzhi Yin*, Tong Chen, Miao Xu, Quoc Viet Hung Nguyen, Jiangning Song. "Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent". IEEE Journal of Biomedical and Health Informatics (JBHI) 2022. (Corresponding author; CORE Rank A*, Q1 Journal)

Yi Cui, Feifei Bai, Hongzhi Yin, Tong Chen, David Dart, Matthew Zillmann, Ryan K. L. Ko. "Multiscale Adaptive Multifractal Detrended Fluctuation Analysis-Based Source Identification of Synchrophasor Data". IEEE Transactions on Smart Grid, 2022. (Q1 Journal)

Feifei Bai, Yi Cui, Ruifeng Yan, Hongzhi Yin, Tong Chen, David Dart, Jalil Yaghoobi. "Cost-Effective Synchrophasor Data Source Authentication Based on Multiscale Adaptive Coupling Correlation Detrended Analysis".  International Journal of Electrical Power and Energy Systems, 2022. (Q1 Journal)

Kaili Li, Haoran Duan, Linfeng Liu, Ruihong Qiu, Ben van den Akker, Bing-Jie Ni, Tong Chen, Hongzhi Yin, Zhiguo Yuan and Liu Ye. "An integrated first principal and deep learning approach for modelling nitrous oxide emissions from wastewater treatment plants". Environmental Science & Technology. 2022. (Q1 Journal, IF:9.028)

Yi Cui, Feifei Bai, Ruifeng Yan, Tapan Saha, Mehdi Mosadeghy, Hongzhi Yin, Ryan K L Ko. "Multifractal Characterization of Distribution Synchrophasors for Cybersecurity Defense of Smart Grids". IEEE Transactions on Smart Grid 2022. (Q1 Journal, IF:8.96)

Guanhua Ye, Hongzhi Yin*, Tong Chen, Hongxu Chen, Lizhen Cui, Xiangliang Zhang. "FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection".IEEE Journal of Biomedical and Health Informatics, 2021. (JBHI'21). (Corresponding author, Q1 Journal, CORE Rank A*)

Zhenchao Sun, Hongzhi Yin*, Hongxu Chen, Tong Chen, Lizhen Cui, Fan Yang. "Disease Prediction via Graph Neural Networks".IEEE Journal of Biomedical and Health Informatics, 2020. (JBHI'20). (Corresponding author, Q1 Journal, CORE Rank A*)

Leila Khalatbari, MR Kangavari, Saeid Hosseini, Hongzhi Yin, Ngai-Man Cheung. "MCP: a Multi-Component Learning Machine to Predict Protein Secondary Structure". Journal Computers in Biology and Medicine. 2019. (Impact Factor:2.1).

Kangzhi Zhao, Yong Zhang, Zihao Wang, Hongzhi Yin*, Xiaofang Zhou, Jin Wang and Chunxiao Xing. "Modeling Patient Visit Using Electronic Medical Records for Cost Profile Estimation". DASFAA'18, Gold Coast, Australia, 2018. (CCF Rank B).

Zongwei Wang, Junliang Yu, Min Gao, Hongzhi Yin*, Bin Cui, Shazia Sadiaq. "Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks". The 30th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'24), 25-29 August, 2024, Barcelona, Spain. (CCF Rank A, CORE Rank A*; Corresponding Author).

Yi Liu, Hongrui Xuan, Bohan Li, Meng Wang, Tong Chen and Hongzhi Yin*. "Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph". The 32nd ACM International Conference on Information and Knowledge Management  (CIKM'23), 21-25 October 2023, Birmingham, UK. (CCF Rank B, CORE Rank A; Corresponding Author)

Junliang Yu, Hongzhi Yin*, Xin Xia, Tong Chen, Jundong Li, Zi Huang. "Self-Supervised Learning for Recommender Systems: A Survey". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)

Hongrui Xuan, Yi Liu, Bohan Li, Hongzhi Yin*. "Knowledge Enhancement for Contrastive Multi-Behavior Recommendation". The 16th ACM International WSDM Conference (WSDM'23), Singapore, February 27 to March 3, 2023.

Bowen Hao, Hongzhi Yin*, Jing Zhang, Cuiping Li, Hong Chen. "A Multi-Strategy based Pre-Training Method for Cold-Start Recommendation". ACM Transactions on Information Systems. 2022. (TOIS'22). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal)

Junliang Yu, Hongzhi Yin*, Xin Xia, Tong Chen, Lizhen Cui and Quoc Viet Hung Nguyen . "Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation". The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'22), July, 2022. (CCF Rank A, CORE Rank A*; Corresponding author).

Ruihong Qiu, Zi Huang, Hongzhi Yin*, Zijian Wang. "Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation". The 15th ACM International WSDM Conference (WSDM'22), March, 2022. (CCF Rank B, CORE Rank A*, corresponding author).

Junliang Yu, Hongzhi Yin*, Min Gao, Xin Xia, Xiangliang Zhang, Quoc Viet Hung Nguyen. "Socially-Aware Self-Supervised Tri-Training for Recommendation". The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'21), Singapore. August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Junliang Yu, Hongzhi Yin*, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung and Xiangliang Zhang. "Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation". The Web Conference 2021 (WWW'21), April, 2021. (CCF Rank A, CORE Rank A*, Codes; Corresponding author and contributing equally with the first author).

Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li and Hong Chen. "Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation". The 14th ACM International WSDM Conference (WSDM'21), March, 2021. (CCF Rank B, CORE Rank A*).

Xin Xia, Hongzhi Yin*, Junliang Yu, Qinyong Wang, Lizhen Cui, and Xiangliang Zhang. "Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation". Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI'21), Feburary, 2021. (CCF Rank A, CORE Rank A*; Corresponding Author).

Ruihong Qiu, Zi Huang, Hongzhi Yin*. "Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation".  The 21st IEEE International Conference on Data Mining (ICDM'21),  December 2021. (CCF Rank B, CORE Rank A*; Corresponding author) 

Xin Xia, Hongzhi Yin*, Junliang Yu, Yingxia Shao,  and Lizhen Cui. "Self-Supervised Co-Training for Session-based Recommendation".  The 30th ACM International Conference on Information and Knowledge Management (CIKM'21), October, 2021. (CCF Rank B, CORE Rank A; Corresponding author and contributing equally with the first author).

Junwei Zhang, Min Gao, Junliang Yu, Lei Guo, Jundong Li and  Hongzhi Yin. "Double-Scale Self-Supervised Hypergraph Convolutional Network for Group Recommendation ".  The 30th ACM International Conference on Information and Knowledge Management (CIKM'21), October, 2021. (CCF Rank B, CORE Rank A)

Ruiqi Zheng, Liang Qu, Tong Chen, Kai Zheng, Yuhui Shi, Hongzhi Yin*. "Personalized Elastic Embedding Learning for On-Device Recommendation".  Accepted by IEEE Transactions on Knowledge and Data Engineering. 2024. (TKDE'24). (CCF Rank A, CORE Rank A*, Q1 Journal)

Yunke Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Budgeted Embedding Table For Recommender Systems". The 17th ACM International Conference on Web Search and Data Mining (WSDM'24), March 4-8, 2024, Mérida, México. (CORE Rank A, CCF Rank B, Tsinghua Rank A; Corresponding Author)

Ruiqi Zheng, Liang Qu, Bin Cui, Yuhui Shi, Hongzhi Yin*.  "AutoML for Deep Recommender Systems: A Survey". ACM Transactions on Information Systems. 2023. (TOIS'23). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Liang Qu, Yonghong Ye, Ningzhi Tang, Lixin Zhang, Yuhui Shi and Hongzhi Yin*. "Single-shot Embedding Dimension Search in Recommender System" . The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'22), July, 2022. (CCF Rank A, CORE Rank A*; Corresponding author).

Tong Chen, Hongzhi Yin*, Yujia Zheng, Zi Huang, Yang Wang, Meng Wang. "Learning Elastic Embeddings for Customizing On-Device Recommenders". The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'21), Singapore. August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Xin Xia, Junliang Yu, Qinyong Wang, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin*.  "Efficient On-Device Session-Based Recommendation". ACM Transactions on Information Systems. 2023. (TOIS'23). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Hongrui Xuan, Yi Liu, Bohan Li, Hongzhi Yin*. "Knowledge Enhancement for Contrastive Multi-Behavior Recommendation". The 16th ACM International WSDM Conference (WSDM'23), Singapore, February 27 to March 3, 2023.

Ruihong Qiu, Zi Huang, Hongzhi Yin*. "Beyond Double Ascent via Recurrent Neural Tangent Kernel in Sequential Recommendation". The 22nd IEEE International Conference on Data Mining (ICDM'22), November, 2022. (CCF Rank B, CORE Rank A*; Corresponding author).

Ruihong Qiu, Zi Huang, Hongzhi Yin*, Zijian Wang. "Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation". The 15th ACM International WSDM Conference (WSDM'22), March, 2022. (CCF Rank B, CORE Rank A*, corresponding author).

Ruihong Qiu, Zi Huang, Tong Chen, Hongzhi Yin*. "Exploiting Positional Information for Session-based Recommendation". ACM Transactions on Information Systems. 2021. (TOIS'21). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal)

Xin Xia, Hongzhi Yin*, Junliang Yu, Qinyong Wang, Lizhen Cui, and Xiangliang Zhang. "Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation". Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI'21), Feburary, 2021. (CCF Rank A, CORE Rank A*; Corresponding Author).

Ruihong Qiu, Zi Huang, Hongzhi Yin*. "Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation".  The 21st IEEE International Conference on Data Mining (ICDM'21),  December 2021. (CCF Rank B, CORE Rank A*; Corresponding author) 

Xin Xia, Hongzhi Yin*, Junliang Yu, Yingxia Shao,  and Lizhen Cui. "Self-Supervised Co-Training for Session-based Recommendation".  The 30th ACM International Conference on Information and Knowledge Management (CIKM'21), October, 2021. (CCF Rank B, CORE Rank A; Corresponding author and contributing equally with the first author).

Yang Li, Tong Chen, Pengfei Zhang, Hongzhi Yin. "Lightweight Self-Attentive Sequential Recommendation ".  The 30th ACM International Conference on Information and Knowledge Management (CIKM'21), October, 2021. (CCF Rank B, CORE Rank A).

Yi Liu, Bohan Li, Yalei Zang, Aoran Li and Hongzhi Yin. "A Knowledge-Aware Recommender with Attention-Enhanced Dynamic Convolutional Network".  The 30th ACM International Conference on Information and Knowledge Management (CIKM'21), October, 2021. (CCF Rank B, CORE Rank A).

Ruihong Qiu, Hongzhi Yin*, Tong Chen, Zi Huang. "GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation". 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR'2020), Xian, China. July, 2020. (CCF Rank A, CORE Rank A* , Corresponding author; Contributing equally with the first author).

Ruihong Qiu, Zi Huang, Jingjing Li, Hongzhi Yin*. "Exploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks". ACM Transaction on Information Systems. 2020. (TOIS'20). (Corresponding author and having equal contribution with the first author, CCF Rank A, CORE Rank A, Q1 Journal) 

Lei Guo, Hongzhi Yin*, Qinyong Wang, Tong Chen, Alexander Zhou and Nguyen Quoc Viet Hung. "Streaming Session-based Recommendation". 25th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'19), Anchorage, Alaska, August, 2019. (CCF Rank A, CORE Rank A*, Oral, Acceptance Rate=9%, slides; Corresponding author and contributing equally with the first author).

Kangzhi Zhao, Yong Zhang, Hongzhi Yin*, Jin Wang, Kai Zheng, Xiaofang Zhou, and Chunxiao Xing. "Discovering Subsequence Patterns for Next POI Recommendation". The 29th International Joint Conference on Artificial Intelligence(IJCAI'2020), Yokohama, Japan. July, 2020. (CCF Rank A, CORE Rank A*, Acceptance rate 12.6%, Corresponding Author).

Tong Chen, Hongzhi Yin*, Quoc Viet Hung Nguyen, Wen-Chih Peng, Xue Li and Xiaofang Zhou. "Sequence-Aware Factorization Machines for Temporal Predictive Analytics". 36th IEEE International Conference on Data Engineering(ICDE'2020), Dallas, Texas. April, 2020. (CCF Rank A, CORE Rank A* , Corresponding author and supervisor of the first author; Contributing equally with the first author).

Tong Chen, Hongzhi Yin*, Hongxu Chen, Rui Yan, Quoc Viet Hung Nguyen, Xue Li. "AIR: Attentional Intention-Aware Recommender Systems". 35th IEEE International Conference on Data Engineering (ICDE'19), Macau SAR. April, 2019. (CCF Rank A, CORE Rank A*, Slides, Codes Download).

Ke Sun, Tieyun Qian, Hongzhi Yin*, Tong Chen, Yiqi Chen and Ling Chen. "What Can History Tell Us? Identifying Relevant Sessions for Next-Item Recommendation". The 28th ACM International Conference on Information and Knowledge Management (CIKM'19), Beijing, China, October, 2019. (CCF Rank B, CORE Rank A).

Ruihong Qiu, Jingjing Li, Zi Huang and Hongzhi Yin*. "Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks". The 28th ACM International Conference on Information and Knowledge Management (CIKM'19), Beijing, China, October, 2019. (CCF Rank B, CORE Rank A, Codes).

Qinyong Wang, Hongzhi Yin*, Zhiting Hu, Defu Lian, Hao Wang and Zi Huang. "Neural Memory Streaming Recommender Networks with Adversarial Training". 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), London, United Kingdom. August, 2018. (CCF Rank A, CORE Rank A*, Codes Download. The first author is supervised by Dr. Hongzhi Yin).

Weiqing Wang, Hongzhi Yin*, Xingzhong Du, Nguyen Quoc Viet Hung, Xiaofang Zhou. "TPM: A Temporal Personalized Model for Spatial Item Recommendation". ACM Transactions on Intelligent Systems and Technology. 2018. (TIST'18).(5-year Impact Factor: 10.47. The first author was supervised by Hongzhi Yin.)

Weiqing Wang, Hongzhi Yin*, Shazia Sadiq, Ling Chen, Min Xie, Xiaofang Zhou. "SPORE: A Sequential Personalized Spatial Item Recommender System". The 32nd IEEE International Conference on Data Engineering (ICDE'16), Helsinki, Finland, May, 2016. (Full research paper, CCF Rank A, CORE Rank A*, Slides Download, The first author was Dr Hongzhi Yin's Phd student. Codes Download)

Xin Xia, Junliang Yu, Guandong Xu and Hongzhi Yin*. "Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation". The 32nd ACM International Conference on Information and Knowledge Management  (CIKM'23), 21-25 October 2023, Birmingham, UK. (CCF Rank B, CORE Rank A; Corresponding Author)

Yunke Qu, Tong Chen, Xiangyu Zhao, Lizhen Cui, Kai Zheng, Hongzhi Yin*. "Continuous Input Embedding Size Search For Recommender Systems". The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23), Taipei,  23-27 July, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Xin Xia, Junliang Yu, Qinyong Wang, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin*.  "Efficient On-Device Session-Based Recommendation". ACM Transactions on Information Systems. 2023. (TOIS'23). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

 Xin Xia, Hongzhi Yin*, Junliang Yu, Qinyong Wang, Guandong Xu and Quoc Viet Hung Nguyen . "On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation". The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'22), July, 2022. (CCF Rank A, CORE Rank A*; Corresponding author).

Tong Chen, Hongzhi Yin*, Yujia Zheng, Zi Huang, Yang Wang, Meng Wang. "Learning Elastic Embeddings for Customizing On-Device Recommenders". The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'21), Singapore. August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Tong Chen, Hongzhi Yin*, Xiangliang Zhang, Zi Huang, Yang Wang, Meng Wang. "Quaternion Factorization Machines: A Lightweight Solution to Intricate Feature Interaction Modelling" . IEEE Transactions on Neural Networks and Learning Systems. (Corresponding author; CORE Rank A*, Q1 Journal) 

Yang Li, Tong Chen, Pengfei Zhang, Hongzhi Yin. "Lightweight Self-Attentive Sequential Recommendation ".  The 30th ACM International Conference on Information and Knowledge Management (CIKM'21), October, 2021. (CCF Rank B, CORE Rank A).

Pengfei Zhang, Jiasheng Duan, Zi Huang, Hongzhi Yin. "Joint-teaching: Learning to Refine Knowledge for Resource-constrained Unsupervised Cross-modal Retrieval". The 29th ACM International Conference on Multimedia (MM'21), 2021.  (CCF Rank A, CORE Rank A*)

Qinyong Wang, Hongzhi Yin*, Tong Chen, Zi Huang, Hao Wang, Yanchang Zhao, Quoc Viet Hung Nguyen. "Next Point-of-Interest Recommendation on Resource-Constrained Mobile Devices". The Web Conference 2020 (WWW'2020), Taipei, Taiwan. April, 2020. (CCF Rank A, CORE Rank A*, Acceptance Rate 19% , Corresponding author and supervisor of the first author; Contributing equally with the first author).

Yan Zhang, Ivor W. Tsang, Hongzhi Yin*, Guowu Yang, Defu Lian, Jingjing Li. "Deep Pairwise Hashing for Cold-start Recommendation". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (Corresponding author, CCF Rank A, CORE Rank A*)

Yan Zhang, Haoyu Wang, Defu Lian, Ivor W. Tsang, Hongzhi Yin, Guowu Yang. "Discrete Ranking-based Matrix Factorization with Self-Paced Learning". 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), London, United Kingdom. August, 2018. (CCF Rank A, CORE Rank A*. ).

Yan Zhang, Hongzhi Yin*, Zi Huang, Xingzhong Du, Guowu Yang and Diefu Lian. "Discrete Deep Learning for Fast Content-Aware Recommendation". Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining (WSDM'18), Marina Del Rey, CA, USA, 2018. (CCF Rank B, CORE Rank A*, Slides Download, Codes Download).

Thanh Toan Nguyen, Quoc Viet Hung Nguyen, Thanh Tam Nguyen, Thanh Trung Huynh, Thanh Thi Nguyen, Matthias Weidlich, Hongzhi Yin. "Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures" . ACM Computing Surveys (CSUR) 2024. (CCF Rank A, CORE Rank A*, Q1 Journal) 

Zongwei Wang, Junliang Yu, Min Gao, Hongzhi Yin*, Bin Cui, Shazia Sadiaq. "Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks". The 30th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'24), 25-29 August, 2024, Barcelona, Spain. (CCF Rank A, CORE Rank A*; Corresponding Author).

Lijian Chen, Wei Yuan, Tong Chen, Guanhua Ye,  Quoc Viet Hung Nguyen, Hongzhi Yin*. "Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion". ACM Transactions on Information Systems. 2024. (TOIS'24). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Ruiqi Zheng, Liang Qu, Tong Chen, Kai Zheng, Yuhui Shi and Hongzhi Yin*. "Poisoning Decentralized Collaborative Recommender System and Its Countermeasures". The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'24), July 14-18, 2024, Washington D.C., USA.

Wei Yuan, Chaoqun Yang, Liang Qu, Quoc Viet Hung Nguyen, Jianxin Li, Hongzhi Yin*.  "Hide Your Model: A Parameter Transmission-free Federated Recommender System". The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Liang Qu, Wei Yuan, Ruiqi Zheng, Lizhen Cui, Yuhui Shi, Hongzhi Yin*. "Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Ruiqi Zheng, Liang Qu, Tong Chen, Lizhen Cui, Yuhui Shi, Hongzhi Yin*. "Decentralized Collaborative Learning with Adaptive Reference Data for On-Device POI Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Jing Long, Tong Chen, Guanhua Ye, Kai Zheng, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Physical Trajectory Inference Attack and Defense in Decentralized POI Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Wei Yuan, Shilong Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Manipulating Visually-aware Federated Recommender Systems and Its Countermeasures" . ACM Transactions on Information Systems. 2024. (TOIS'24). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal) 

Sixiao Zhang, Hongzhi Yin*, Hongxu Chen, Cheng Long. "Defense Against Model Extraction Attacks on Recommender Systems".  The 17th ACM International Conference on Web Search and Data Mining (WSDM'24), March 4-8, 2024, Mérida, México. (CORE Rank A, CCF Rank B, Tsinghua Rank A; Corresponding Author)

Shijie Zhang, Wei Yuan, Hongzhi Yin*. "Comprehensive Privacy Analysis on Federated Recommender System against Attribute Inference Attacks". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)

Zongwei Wang, Min Gao, Wentao Li, Junliang Yu, LinXin Guo, Hongzhi Yin*. "Efficient Bi-Level Optimization for Recommendation Denoising". The 29th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'23), 6-10 August, 2023, Long Beach, CA, USA. (CCF Rank A, CORE Rank A*; Corresponding Author).

Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, Hongzhi Yin*.  "Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures". The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23), Taipei,  23-27 July, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Lizhen Cui, Tieke He, Hongzhi Yin*. "Interaction-level Membership Inference Attack Against Federated Recommender Systems".  International World Wide Web Conference 2023 (WWW'23), AUSTIN, TEXAS, USA, APRIL 30 - MAY 4, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Wei Yuan, Hongzhi Yin*, Fangzhou Wu, Shijie Zhang, Tieke He, Hao Wang. "Federated Unlearning for On-Device Recommendation". The 16th ACM International WSDM Conference (WSDM'23), Singapore, February 27 to March 3, 2023.

Shijie Zhang, Hongzhi Yin*,  Tong Chen, Zi Huang, Quoc Viet Hung Nguyen, Lizhen Cui. "PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion".  The 15th ACM International WSDM Conference (WSDM'22), March, 2022. (CCF Rank B, CORE Rank A*, corresponding author).

Qinyong Wang,  Hongzhi Yin*, Tong Chen, Junliang Yu, Alexander Zhou and Xiangliang Zhang. "Fast-adapting and Privacy-preserving Federated Recommender System". The VLDB Journal 2021. (VLDBJ'21). (Corresponding author; CCF Rank A, CORE Rank A*, Q1 Journal)

Shijie Zhang, Hongzhi Yin*, Tong Chen, Zi Huang, Lizhen Cui and Xiangliang Zhang. "Graph Embedding for Recommendation against Attribute Inference Attacks". The Web Conference 2021 (WWW'21), April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Peng-Fei Zhang, Yang Li, Zi Huang and Hongzhi Yin. "Privacy Protection in Deep Multi-modal Retrieval". The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), July, 2021. (CCF Rank A, CORE Rank A*).

Pengfei Zhang, Guangdong Bai, Hongzhi Yin, Zi Huang. "Proactive Privacy-preserving Learning for Cross-modal Retrieval".  ACM Transactions on Information Systems. 2022. (TOIS'22). (CCF Rank A, CORE Rank A, Q1 Journal)

Shijie Zhang, Hongzhi Yin*, Tong Chen, Nguyen Quoc Viet Hung, Zi Huang and Lizhen Cui. "GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Identification". 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR'2020), Xian, China. July, 2020. (CCF Rank A, CORE Rank A*, Codes, Corresponding author and supervisor of the first author; Contributing equally with the first author).

Yanzhang Lv, Hongzhi Yin*, Jun Liu, Mengyue Liu, Huan Liu, Shizhuo Deng. "Reliable Recommendation with Review-level Explanations". IEEE 37th International Conference on Data Engineering (ICDE'21), Greece, April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Hongxu Chen, Yicong Li, Xiangguo Sun, Guandong Xu and Hongzhi Yin. "Temporal Meta-path Guided Explainable Recommendation". The 14th ACM International WSDM Conference (WSDM'21), March, 2021. (CCF Rank B, CORE Rank A*; Corresponding author).

Zhihong Cui, Hongxu Chen, Lizhen Cui, Shijun Liu, Xueyan Liu, Guandong Xu, Hongzhi Yin. "Reinforced KGs Reasoning for Explainable Sequential Recommendation".  World Wide Web Journal (WWWJ), 2021. (CCF Rank B, CORE Rank A.)

Tong Chen, Hongzhi Yin*, Guanhua Ye, Zi Huang, Yang Wang and Meng Wang. "Try This Instead: Personalized and Interpretable Substitute Recommendation". 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR'2020), Xian, China. July, 2020. (CCF Rank A, CORE Rank A*, Codes, Corresponding author and supervisor of the first author; Contributing equally with the first author).

Yanzhang Lv, Hongzhi Yin*, Jun Liu, Mengyue Liu, Huan Liu, Shizhuo Deng. "Reliable Recommendation with Review-level Explanations". IEEE 37th International Conference on Data Engineering (ICDE'21), Greece, April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Xuhui Ren, Tong Chen, Quoc Viet Hung Nguyen, Lizhen Cui, Zi Huang, Hongzhi Yin*. "Explicit Knowledge Graph Reasoning for Conversational Recommendation".  ACM Transactions on Intelligent Systems and Technology 2024. (TIST'24, Corresponding author, Q1 Journal) 

Xuhui Ren, Hongzhi Yin*, Tong Chen, Hao Wang, Zi Huang and Kai Zheng. "Learning to Ask Appropriate Questions in Conversational Recommendation". The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), July, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Chen Zhang, Hao Wang, Feijun Jiang and Hongzhi Yin*. "Adapting to Context-Aware Knowledge in Natural Conversation for Multi-Turn Response Selection". The Web Conference 2021 (WWW'21), April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author).

Xuhui Ren, Hongzhi Yin*, Tong Chen, Hao Wang, Nguyen Quoc Viet Hung, Zi Huang, Xiangliang Zhang. "CRSAL: Conversational Recommender Systems with Adversarial Learning". ACM Transactions on Information Systems. 2020. (TOIS'20). (Corresponding author and having equal contribution with the first author, CCF Rank A, CORE Rank A)

Qinyong Wang, Hongzhi Yin*, Weiqing Wang, Zi Huang, Guibing Guo and Quoc Viet Hung Nguyen. "Multi-Hop Path Queries over Knowledge Graphs with Neural Memory Networks". The 24th International Conference on Database Systems for Advanced Applications (DASFAA'19), Chiang Mai, Thailand. April, 2019. (CCF Rank B)

Jing Long, Guanhua Ye,  Tong Chen, Yang Wang, Meng Wang, Hongzhi Yin*. "Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations". The 30th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'24), 25-29 August, 2024, Barcelona, Spain. (CCF Rank A, CORE Rank A*; Corresponding Author).

Jiangnan Xia,Yu Yang,Senzhang Wang,Hongzhi Yin,Jiannong Cao, PhilipS.Yu. "Bayes-enhanced Multi-view Attention Networks for Robust POI Recommendation". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2024. (TKDE'24). (CCF Rank A, CORE Rank A*, Q1 Journal)

Huynh Thanh Trung, Tong Van Vinh, Nguyen Thanh Tam, Jun Jo, Hongzhi Yin, Quoc Viet Hung Nguyen. "Learning Holistic Interactions in LBSNs with High-order, Dynamic, and Multi-role Contexts". IEEE Transactions on Knowledge and Data Engineering. 2022. (TKDE'22). (CCF Rank A, CORE Rank A*, Q1 Journal)

Yang Li, Tong Chen, Yadan Luo, Hongzhi Yin, Zi Huang. "Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation". The 30th International Joint Conference on Artificial Intelligence (IJCAI'21), August, 2021. (CCF Rank A, CORE Rank A*).

Yue Cui, Hao Sun, Yan Zhao, Hongzhi Yin and Kai Zheng. "Sequential-knowledge-aware Next POI Recommendation: A Meta-learning Approach". ACM Transactions on Information Systems. 2021. (TOIS'21). (CCF Rank A, CORE Rank A, Q1 Journal)

Qinyong Wang, Hongzhi Yin*, Tong Chen, Zi Huang, Hao Wang, Yanchang Zhao, Quoc Viet Hung Nguyen. "Next Point-of-Interest Recommendation on Resource-Constrained Mobile Devices". The Web Conference 2020 (WWW'2020), Taipei, Taiwan. April, 2020. (CCF Rank A, CORE Rank A*, Acceptance Rate 19% , Corresponding author and supervisor of the first author; Contributing equally with the first author).

Kangzhi Zhao, Yong Zhang, Hongzhi Yin*, Jin Wang, Kai Zheng, Xiaofang Zhou, and Chunxiao Xing. "Discovering Subsequence Patterns for Next POI Recommendation". The 29th International Joint Conference on Artificial Intelligence(IJCAI'2020), Yokohama, Japan. July, 2020. (CCF Rank A, CORE Rank A*, Acceptance rate 12.6%, Corresponding Author).

Ke Sun, Tieyun Qian, Tong Chen, Yile Liang, Quoc Viet Hung Nguyen, Hongzhi Yin*. "Where to Go Next: Modeling Long and Short Term User Preferences for Point-of-Interest Recommendation". The Thirty-Third AAAI Conference on Artificial Intelligence(AAAI'2020), New York, USA. February, 2020. (CCF Rank A, CORE Rank A*, Codes , Corresponding author and contributing equally with the first author).

Guohui Li, Qi Chen, Bolong Zheng, Hongzhi Yin, Nguyen Quoc Viet Hung. "Group based Recurrent Neural Networks for POI Recommendation". ACM Transactions on Data Science. 2020. (TDS'20).

Jianxin Liao, Tongcun Liu, Hongzhi Yin, Tong Chen, Jingyu Wang. "An Integrated Model based on Deep Multimodal and Rank Learning for Point-of-Interest Recommendation". World Wide Web Journal (WWWJ), 2021. (CCF Rank B, CORE Rank A.)

Tieyun Qian, Bei Liu, Nguyen Quoc Viet Hung, Hongzhi Yin*. "Spatiotemporal Representation Learning for Translation-based POI Recommendation". ACM Transaction on Information Systems. 2019. (TOIS'19). (Corresponding author and having equal contribution with the first author, CCF Rank A, CORE Rank A)

Weiqing Wang, Hongzhi Yin*. "Spatio-temporal Recommendation with Big Geo-social Networking Data", Chapter 24 in "Big Data Recommender Systems: Recent Trends and Advances". The Institution of Engineering and Technology, 2019.

Hongzhi Yin*, Bin Cui, Xiaofang Zhou. "Spatio-Temporal Recommendation in Geo-Social Networks" in "Encyclopedia of Social Network Analysis and Mining". Springer, 2018.

Weiqing Wang, Hongzhi Yin*, Xingzhong Du, Nguyen Quoc Viet Hung, Xiaofang Zhou. "TPM: A Temporal Personalized Model for Spatial Item Recommendation". ACM Transactions on Intelligent Systems and Technology. 2018. (TIST'18).(5-year Impact Factor: 10.47. The first author was supervised by Hongzhi Yin.)

Saeid Hosseini, Hongzhi Yin, Xiaofang Zhou, Shazia Sadiq, Mohammad Reza Kangavari, Ngai-Man Cheung . "Leveraging Multi-aspect Time-related Influence in Location Recommendation". World Wide Web Journal (WWWJ), 2018. (CCF Rank B, CORE Rank A.)

Hongzhi Yin*, Weiqing Wang, Hao Wang, Ling Chen, Xiaofang Zhou. "Spatial-Aware Hierarchical Collaborative Deep Learning for POI Recommendation". IEEE Transaction on Knowledge and Data Engineering. 2017. (TKDE'17). (CCF Rank A,ERA Rank A, Codes Download)

Hao Wang, Yanmei Fu, Qinyong Wang, Changying Du, Hongzhi Yin* and Hui Xiong. "A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Mobile Users". Proc. of 2017 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'17),Halifax, Nova Scotia, Canada, 2017. (CCF Rank A, CORE Rank A*).

Hongzhi Yin*, Zhiting Hu, Xiaofang Zhou, Hao Wang, Kai Zheng, Quoc Viet Hung Nguyen. "Discovering Interpretable Geo-Social Communities for User Behavior Prediction". The 32nd IEEE International Conference on Data Engineering (ICDE'16), Helsinki, Finland, May, 2016. (Full research paper, CCF Rank A, CORE Rank A*, Slides Download, Codes(PWD:nm0t)).

Weiqing Wang, Hongzhi Yin*, Ling Chen, Yizhou Sun, Shazia Sadiq, Xiaofang Zhou. "ST-SAGE: A Spatial-Temporal Sparse Additive Generative Model for Spatial Item Recommendation". ACM Transactions on Intelligent Systems and Technology. 2017. (TIST'17). ( 5-year Impact Factor: 10.47. The first author was supervised by Hongzhi Yin.)

Yizhou Sun, Xiang Ren, Hongzhi Yin. "Content-rich recommendation: Integrating Network, Text and Spatial-Temporal Dimensions". Proc. of 2017 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'17),Halifax, Nova Scotia, Canada, 2017. (Tutorial, CCF Rank A, CORE Rank A*).

Hongzhi Yin*, Bin Cui, Xiaofang Zhou, Weiqing Wang, Zi Huang, Shazia Sadiq. "Joint Modeling of User Check-in Behaviors for Real-time Point-of-Interest Recommendation". ACM Transaction on Information Systems. 2016. (TOIS'16). (CCF Rank A,ERA Rank A)

Weiqing Wang, Hongzhi Yin*, Shazia Sadiq, Ling Chen, Min Xie, Xiaofang Zhou. "SPORE: A Sequential Personalized Spatial Item Recommender System". The 32nd IEEE International Conference on Data Engineering (ICDE'16), Helsinki, Finland, May, 2016. (Full research paper, CCF Rank A, CORE Rank A*, Slides Download, The first author was Dr Hongzhi Yin's Phd student. Codes Download)

Min Xie, Hongzhi Yin*, Fanjiang Xu, Hao Wang, Weitong Chen and Sen Wang. "Learning Graph-based POI Embedding for Location-based Recommendation". The 25th ACM International Conference on Information and Knowledge Management(CIKM'16), Hyatt Hotel, Indianapolis, United States, 2016. (Full research paper,Acceptance rate: 17.6%, CORE Rank A, CCF Rank B, Slides Download,, The first author was supervised by Dr Hongzhi Yin. Codes Download)

Hongzhi Yin*, Xiaofang Zhou, Bin Cui, Hao Wang, Kai Zheng, Quoc Viet Hung Nguyen. Adapting to User Interest Drift for POI Recommendation". IEEE Transaction on Knowledge and Data Engineering. 2016. (TKDE'16). (CCF Rank A,CORE Rank A, Codes Download)

Hongzhi Yin*, Bin Cui. "Spatio-Temporal Recommendation in Social Media". Springer, ISBN: 978-981-10-0747-7.2016.

Hongzhi Yin*, Bin Cui, Ling Chen, Zhiting Hu, Xiaofang Zhou. "Dynamic User Modeling in Social Media Systems". ACM Transaction on Information Systems. 2015. (TOIS, CCF Rank A, CORE Rank A)

Hongzhi Yin*, Bin Cui, Ling Chen, Zhiting Hu, Chengqi Zhang. "Modeling Location-based User Rating Profiles for Personalized Recommendation". ACM Trans. Knowl. Discov. Data. 2015. (TKDD, SCI, CCF Rank B, Code Download)

Hongzhi Yin*, Bin Cui, Yizhou Sun, Zhiting Hu, Ling Chen. "LCARS: A Spatial Item Recommender System". ACM Transaction on Information Systems. 2014. (TOIS, CCF Rank A, CORE Rank A, Code Download)

Hongzhi Yin*, Xiaofang Zhou, Yingxia Shao, Hao Wang, Shazia Sadiq. "Joint Modeling of User Check-in Behaviors for Point-of-Interest Recommendation " . The 24th ACM International Conference on Information and Knowledge Management (CIKM'15), Melbourne, Australia, October, 2015. (Full research paper, Acceptance rate: 17.9%, CCF Rank B, CORE Rank A, Slides Download, Codes Download)

Weiqing Wang, Hongzhi Yin*, Ling Chen, Yizhou Sun, Shazia Sadiq, Xiaofang Zhou. "Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation" . Proc. of 2015 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'15), Sydney, Australia, August, 2015. (Full research paper, Acceptance rate: 19.3%, CCF Rank A, CORE Rank A*, Slides Download,,The first author was Dr Hongzhi Yin's Phd student, Code Download)

Hongzhi Yin*, Bin Cui, Zi Huang, Weiqing Wang,  Xian Wu,  Xiaofang Zhou. "Joint Modeling of Users’ Interests and Mobility Patterns for Point-of-Interest Recommendation". The 2015 ACM Multimedia Conference(ACM-MM'15), Brisbane, Australia, October, 2015. (CCF Rank A, CORE Rank A*, Code Download).

Hongzhi Yin*, Bin Cui, Ling Chen, Zhiting Hu, Zi Huang. "A Temporal Context-Aware Model for User Behavior Modeling in Social Media Systems". Proc. Of 2014 ACM SIGMOD Int. Conf. Management of Data (SIGMOD’14), Snowbird, Utah, USA, June, 2014. (Full research paper, CCF Rank A, CORE Rank A*, Slides, Code Download).

Hongzhi Yin*, Yizhou Sun, Bin Cui, Zhiting Hu, Ling Chen. "LCARS: A Location-Content-Aware Recommender System". Proc. of 2013 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD’13), Chicago, IL, Aug. 2013.(Full research paper, Acceptance rate: 9.1%, CCF Rank A, CORE Rank A*, Slides, Code Download, Top 1 cited paper among all KDD-13 oral papers)

Saeid Hosseini, Hongzhi Yin, Meihui Zhang, Xiaofang Zhou and Shazia Sadiq. "Jointly Modeling Heterogeneous Temporal Properties in Location Recommendation".The 22nd International Conference on Database Systems for Advanced Applications(DASFAA'17), Suzhou, China, March, 2017. (Full research paper, CCF Rank B, CORE Rank A).

Qinyong Wang, Hongzhi Yin*, Hao Wang, Zi Huang. "TSAUB: A Temporal-Sentiment-Aware User Behavior Model for Personalized Recommendation". ADC'18, Best Paper Award, Gold Coast, Australia, 2018.

Min Xie, Hongzhi Yin*, Fanjiang Xu, Hao Wang, Xiaofang Zhou. "Graph-based Metric Embedding for Next POI Recommendation" . The 2016 Web Information Systems Engineering(WISE'16), Shanghai, China, 2016. (Full research paper, CORE Rank A, will appear, The first author was supervised by Dr Hongzhi Yin.)

Qinyong Wang, Hongzhi Yin, Hao Wang. "A Time and Sentiment Unification Model for Personalized Recommendation" . APWEB-WAIM 2017, Beijing, China, 2017. (Full research paper, CORE Rank B, CCF Rank C)

Huimin Wu, Jie Shao, Hongzhi Yin, Hengtao Shen, Xiaofang Zhou. "Geographical Constraint and Temporal Similarity Modeling for Point-of-Interest". The 2015 Web Information Systems Engineering(WISE'15), Miami, Florida, USA, December, 2015. (Invited paper, CORE Rank A, CCF Rank C)

Wei Jiang, Xinyi Gao, Guandong Xu, Tong Chen, Hongzhi Yin*.  "Challenging Low Homophily in Social Recommendation". The Web Conference 2024 (WWW'24), May 13-17, 2024, Singapore. (CCF Rank A, CORE Rank A*)

Junliang Yu, Hongzhi Yin*, Min Gao, Xin Xia, Xiangliang Zhang, Quoc Viet Hung Nguyen. "Socially-Aware Self-Supervised Tri-Training for Recommendation". The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'21), Singapore. August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Junliang Yu, Hongzhi Yin*, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung and Xiangliang Zhang. "Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation". The Web Conference 2021 (WWW'21), April, 2021. (CCF Rank A, CORE Rank A*, Codes; Corresponding author and contributing equally with the first author).

Chengyuan Zhang, Yang Wang, Lei Zhu, Jiayu Song, Hongzhi Yin. "MG-HIF: Multi-Graph Heterogeneous Interaction Fusion forSocial Recommendation". ACM Transactions on Information Systems. 2021. (TOIS'21). (CCF Rank A, CORE Rank A, Q1 Journal)

Junliang Yu, Hongzhi Yin*, Jundong Li, Min Gao, Zi Huang, Lizhen Cui. "Enhance Social Recommendation with Adversarial Graph Convolutional Networks". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (Corresponding author and having equal contribution with the first author, CCF Rank A, CORE Rank A*, Q1 Journal,Codes)

Hongxu Chen, Hongzhi Yin*, Tong Chen, Weiqing Wang, Xue Li, Xia Hu. "Social Boosted Recommendation with Folded Bipartite Network Embedding". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (Corresponding author and having equal contribution with the first author, CCF Rank A, CORE Rank A*)

Junliang Yu, Min Gao, Hongzhi Yin*, Jundong Li, Chongming Gao, and Qinyong Wang. "Generating Reliable Friends via Adversarial Training to Improve Social Recommendation". 2019 The IEEE International Conference on Data Mining (ICDM'19), Beijing, China. November 2019. (CCF Rank B, CORE Rank A*, Acceptance Rate=9.08%, Code Download . The first author is supervised by Dr. Hongzhi Yin).

Junliang Yu, Min Gao, Jundong Li, Hongzhi Yin and Huan Liu. "Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation". The 27th ACM International Conference on Information and Knowledge Management (CIKM'18), Turin, Italy, October, 2018. (CCF Rank B, CORE Rank A).

Jiali Yang, Zhixu Li, Hongzhi Yin, Pengpeng Zhao, Lei Zhao, Zhigang Chen and An Liu. "Unified User and Item Representation Learning for Joint Recommendation in Social Network". WISE'18, Dubai, United Arab Emirates, 2018. (CORE Rank A).

Hongzhi Yin, Bin Cui, Hua Lu, Lei Zhao. "Expert Team Finding for Review Assignment ". The 2016 Conference on Technologies and Applications of Artificial Intelligence, (TAAI'16), Hsinchu, Taiwan, 2016. (Full research paper)

Hongzhi Yin*, Bin Cui, Yuxin Huang. "Finding a panel of diverse experts in social networks". Proc. of 2011 Int. Conf. on Advanced Data Mining and Applications (ADMA’11), Beijing, China, Dec. 2011. (Full research paper, Acceptance rate: 18%, CCF Rank C, CORE Rank B)

Bowen Hao, Chaoqun Yang, Lei Guo, Junliang Yu, Hongzhi Yin*. "Motif-based Prompt Learning for Universal Cross-domain Recommendation". The 17th ACM International Conference on Web Search and Data Mining (WSDM'24), March 4-8, 2024, Mérida, México. (CORE Rank A, CCF Rank B, Tsinghua Rank A; Corresponding Author)

Xinyue Liu, Bohan Li, Yijun Chen, Xiaoxue Li, Shuai Xu, Hongzhi Yin. "Disentangled Representations for Cross-Domain Recommendation via Heterogeneous Graph Contrastive Learning".  The 29th International Conference on Database Systems for Advanced Applications (DASFAA'24), July 2-5, Gifu, Japan.

Lei Guo, Jinyu Zhang, Li Tang, Tong Chen, Lei Zhu,  Hongzhi Yin*.  "Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation".  IEEE Transactions on Neural Networks and Learning Systems. 2022. (TNNLs'22)  (Corresponding author; CORE Rank A*, Q1 Journal) 

Lei Guo, Jinyu Zhang, Tong Chen, Xinhua Wang, Hongzhi Yin*.  "Reinforcement Learning-enhanced Shared-account Cross-domain Sequential Recommendation".  IEEE Transactions on Knowledge and Data Engineering. 2022. (TKDE'22). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)

Tong Chen, Hongzhi Yin*, Jing Long, Nguyen Quoc Viet Hung, Yang Wang and Meng Wang. "Thinking inside The Box: Learning Hypercube Representations for Group Recommendation" . The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'22), July, 2022. (CCF Rank A, CORE Rank A*; Corresponding author).

Bowen Hao, Hongzhi Yin*, Cuiping Li, Hong Chen. "Self-supervised Graph Learning for Occasional Group Recommendation".  International Journal of Intelligent Systems. 2022.  (Corresponding author, IF:8.993, Q1 Journal)

Shiqi Wang, Chongming Gao, Min Gao, Junliang Yu, Zongwei Wang, Hongzhi Yin. "Who Are the Best Adopters? User Selection Model for Free Trial Item Promotion". IEEE Transactions on Big Data, 2022.

Hongzhi Yin*, Qinyong Wang, Kai Zheng, Zhixu Li, Xiaofang Zhou. “Overcoming Data Sparsity in Group Recommendation". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (CCF Rank A, CORE Rank A*, Q1 Journal,Code Download)

Hongzhi Yin, Qinyong Wang, Kai Zheng, Zhixu Li, Jiali Yang, Xiaofang Zhou. "Social Influence-based Group Representation Learning for Group Recommendation". 35th IEEE International Conference on Data Engineering (ICDE'19), Macau SAR. April, 2019. (CCF Rank A, CORE Rank A*, Best Paper Award, Slides).

Lei Guo, Hongzhi Yin*, Tong Chen, Xiangliang Zhang, Kai Zheng. "Hierarchical Hyperedge Embedding-based Representation Learning for Group Recommendation". ACM Transactions on Information Systems. 2021. (TOIS'21). (Corresponding author, CCF Rank A, CORE Rank A, Q1 Journal)

Junwei Zhang, Min Gao, Junliang Yu, Lei Guo, Jundong Li and  Hongzhi Yin. "Double-Scale Self-Supervised Hypergraph Convolutional Network for Group Recommendation ".  The 30th ACM International Conference on Information and Knowledge Management (CIKM'21), October, 2021. (CCF Rank B, CORE Rank A)

Lei Guo, Hongzhi Yin*, Qinyong Wang, Bin Cui, Zi Huang and Lizhen Cui. "Group Recommendation with Latent Voting Mechanism". 36th IEEE International Conference on Data Engineering(ICDE'2020), Dallas, Texas. April, 2020. (CCF Rank A, CORE Rank A* , Corresponding author; Contributing equally with the first author).

Li Tang, Lei Guo, Tong Chen, Lei Zhu, Nguyen Quoc Viet Hung and Hongzhi Yin*. "DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation". The 30th International Joint Conference on Artificial Intelligence (IJCAI'21), August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author).

Yan Zhang, Changyu Li, Ivor Tsang, Hui Hu, Lixin Duan, Hongzhi Yin, Wen Li, Jie Shao. "Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations". The 38th  IEEE International Conference on Data Engineering (ICDE'22), May 2022. (CORE Rank A*, CCF Rank A) 

Hongzhi Yin*, Lei Zou, Quoc Viet Hung Nguyen, Zi Huang, and Xiaofang Zhou. "Joint Event-Partner Recommendation in Event-based Social Networks". 34th IEEE International Conference on Data Engineering (ICDE'18), Paris, France 2018. (CCF Rank A, CORE Rank A*, Slides Download, Codes Download).

Hongzhi Yin, Hongxu Chen, Xiaoshuai Sun, Hao Wang, Yang Wang, and Quoc Viet Hung Nguyen. "SPTF: A Scalable Probabilistic Tensor Factorization Model for Semantic-Aware Behavior Prediction". 2017 IEEE International Conference on Data Mining(ICDM'17), New Orleans, USA, November, 2017. (Acceptance Rate:9.5%, Oral, CORE Rank A*, CCF B, Slides Download, Codes Download).

Tong Chen, Hongzhi Yin*, Guanhua Ye, Zi Huang, Yang Wang and Meng Wang. "Try This Instead: Personalized and Interpretable Substitute Recommendation". 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR'2020), Xian, China. July, 2020. (CCF Rank A, CORE Rank A* , Corresponding author and supervisor of the first author; Contributing equally with the first author).

Shijie Zhang, Hongzhi Yin*, Qinyong Wang, Tong Chen, Hongxu Chen and Nguyen Quoc Viet Hung. "Inferring Substitutable Products with Deep Network Embedding". the 28th International Joint Conference on Artificial Intelligence (IJCAI'19), Macao, China, August 2019. (CCF Rank A, CORE Rank A*, Acceptance Rate=17.8%; Corresponding author and supervisor of the first author; Contributing equally with the first author).

Wei Zheng, Bohan Li, Yanan Wang, Hongzhi Yin, Xue Li, Donghai Guan, Xiaolin Qin. "Group Recommender Model Based on Preference Interaction" . ADMA 2017, Singapore, 2017. (Full research paper, CORE Rank B)

Nguyen Thanh Tam, Huynh Thanh Trung, Hongzhi Yin, Matthias Weidlich, Thanh Thi Nguyen, Quoc Viet Hung Nguyen. "Detecting Rumours with Latency Guarantees using Massive Streaming Data". The VLDB Journal 2022. (VLDBJ'22). (CCF Rank A, CORE Rank A*, Q1 Journal)

Ruihong Qiu, Hongzhi Yin*, Tong Chen, Zi Huang. "GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation". 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR'2020), Xian, China. July, 2020. (CCF Rank A, CORE Rank A* , Corresponding author; Contributing equally with the first author).

Lei Guo, Hongzhi Yin*, Qinyong Wang, Tong Chen, Alexander Zhou and Nguyen Quoc Viet Hung. "Streaming Session-based Recommendation". 25th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'19), Anchorage, Alaska, August, 2019. (CCF Rank A, CORE Rank A*, Oral, Acceptance Rate=9%, slides; Corresponding author and contributing equally with the first author).

Weiqing Wang, Hongzhi Yin*, Zi Huang, Qinyong Wang, Xingzhong Du and Quoc Viet Hung Nguyen. "Streaming Ranking Based Recommender Systems". The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'18), Ann Arbor Michigan, U.S.A. July, 2018. (CCF Rank A, CORE Rank A*, Slides Download, Codes Download. The first author is supervised by Dr. Hongzhi Yin).

Chen Chen, Hongzhi Yin, Junjie Yao, Bin Cui. "TeRec: A Temporal Recommender System Over Tweet Stream". Proc. of 2013 Int. Conf. on Very Large Data Bases (VLDB’13), Riva del Garda, Italy, Aug. 2013 (Acceptance rate: 13.2%, CCF Rank A, CORE Rank A*.)

Chi Thang Duong, Dung Hoang, Hongzhi Yin*, Matthias Weidlich, Quoc Viet Hung Nguyen and Karl Aberer. "Efficient Streaming Subgraph Isomorphism with Graph Neural Networks". 47th International Conference on Very Large Data Bases (VLDB'21), August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author).

Thanh Tam Nguyen, Matthias Weidlich, Chi Thang Duong, Hongzhi Yin, Quoc Viet Hung Nguyen. "Retaining data from streams of social platforms with minimal regret". The International Joint Conference on Artificial Intelligence(IJCAI'17),Melbourn, Australia, August, 2017. (CCF Rank A, CORE Rank A*).

Nguyen Thanh Tam, Matthias Weidlich, Bolong Zheng, Hongzhi Yin, Quoc Viet Hung Nguyen, Bela Stantic. "From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms". The Forty-fifth International Conference on Very Large Data Bases (VLDB'19), Los Angeles, California. August, 2019. (CCF Rank A, CORE Rank A* ).

Li He, Xianzhi Wang, Dingxian Wang, Hanyuan Zou, Hongzhi Yin, Guandong Xu. "Simplifying Graph-based Collaborative Filtering for Recommendation". The 16th ACM International WSDM Conference (WSDM'23), Singapore, February 27 to March 3, 2023.

Yile Liang, Tieyun Qian, Qing Li and Hongzhi Yin*. "Enhancing Domain-Level and User-Level Adaptivity in Diversified Recommendation". The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), July, 2021. (CCF Rank A, CORE Rank A*; Corresponding author).

Shitao Xiao, Yingxia Shao, Yawen Li, Hongzhi Yin, Yanyan Shen, Bin Cui."LECF: Recommendation via Learnable Edge Collaborative Filtering". SCIENCE CHINA Information Sciences, 2021. (SCIS'21) (CCF Rank A, Q1 Journal)

Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li and Hong Chen. "Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation". The 14th ACM International WSDM Conference (WSDM'21), March, 2021. (CCF Rank B, CORE Rank A*).

Qinyong Wang, Hongzhi Yin*, Hao Wang, Quoc Viet Hung Nguyen, Zi Huang and Lizhen Cui. "Enhancing Collaborative Filtering with Generative Augmentation". 25th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'19), Anchorage, Alaska, August, 2019. (CCF Rank A, CORE Rank A*, Oral, Acceptance Rate=9%, slides, Codes; Corresponding author and contributing equally with the first author).

Yifan Chen, Yang Wang, Xiang Zhao, Hongzhi Yin*, Ilya Markov, Maarten de Rijke. "Local Variational Feature-based Similarity Models for Recommending Top-N New Items". ACM Transaction on Information Systems, 2020. (TOIS'20). (CCF Rank A, CORE Rank A)

Hongzhi Yin*, Bin Cui, JingLi, Junjie Yao, Chen Chen. "Challenging the Long Tail Recommendation". Proc. of 2012 Int. Conf. on Very Large Data Bases (VLDB’12), Istanbul, Turkey, Aug. 2012. (Full research paper, Acceptance rate: 17.3%, CCF Rank A, CORE Rank A*, Slides, Code Download)

Bowen Hao, Jing Zhang, Cuiping Li, Hong Chen and Hongzhi Yin. "Recommending Courses in MOOCs for Jobs: An Auto Weak Supervision Approach". ECML-PKDD'20, Ghent, Belgium, 2020. (CORE A, CCF Rank B).

Lihong Jiao, Yonghong Yu, Ningning Zhou, Li Zhang and Hongzhi Yin. "Neural Pairwise Ranking Factorization Machine for Item Recommendation". DASFAA'20, Jeju, South Koren, 2020. (CCF Rank B, Short Paper).

Chongming Gao, Shuai Yuan, Zhong Yang, Hongzhi Yin, Junming Shao. "BLOMA: Explain Collaborative Filtering via Boosted Local Rank-One Matrix Approximation". The 24th International Conference on Database Systems for Advanced Applications (DASFAA'19, Short paper), Chiang Mai, Thailand. April, 2019. (CCF Rank B)

Weiqing Wang, Hongzhi Yin*, Zi Huang, Xiaoshuai Sun and Nguyen Quoc Viet Hung. "Restricted Boltzmann Machine Based Active Learning for Sparse Recommendation". DASFAA'18, Gold Coast, Australia, 2018. (CCF Rank B, Slides Download).

Hechuan Wen, Tong Chen, Li Kheng Chai, Shazia Sadiq, Junbin Gao, Hongzhi Yin*. "Variational Counterfactual Prediction under Runtime Domain Corruption". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)  

Dianer Yu, Qian Li, Hongzhi Yin and Guandong Xu. "Causality-guided Graph Learning for Session-based Recommendation". The 32nd ACM International Conference on Information and Knowledge Management  (CIKM'23), 21-25 October 2023, Birmingham, UK. (CCF Rank B, CORE Rank A)

Hechuan Wen, Tong Chen, Li Kheng Chai, Shazia Sadiq, Kai Zheng, Hongzhi Yin*. "To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data". IEEE International Conference on Data Mining 2023 (ICDM'23),  December 1-4, 2023, Shanghai, China. (CCF Rank B, CORE Rank A*; Corresponding Author)

Xinyi Gao, Tong Chen, Wentao Zhang, Yayong Li, Xiangguo Sun, Hongzhi Yin*. "Graph Condensation for Open-World Graph Learning". The 30th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'24), 25-29 August, 2024, Barcelona, Spain. (CCF Rank A, CORE Rank A*; Corresponding Author).

Xinyi Gao, Wentao Zhang, Junliang Yu, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin*. "Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation". The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Xinyi Gao, Tong Chen, Yilong Zhang, Wentao Zhang, Quoc Viet Hung Nguyen, Kai Zheng, Hongzhi Yin*. "Graph Condensation for Inductive Node Representation Learning".  The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Jie Liu, Mengting He, Xuequn Shang, Jieming Shi, Bin Cui, Hongzhi Yin*. "BOURNE: Bootstrapped Self-supervised Learning Framework for Unified Graph Anomaly Detection". The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Wentao Zhang, Xinyi Gao, Ling Yang, Meng Cao, Ping Huang, Jiulong Shan, Hongzhi Yin, Bin Cui. "BIM: Improving Graph Neural Networks with Balanced Influence Maximization". The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Xinyi Gao, Wentao Zhang, Tong Chen, Junliang Yu, Quoc Viet Hung Nguyen and Hongzhi Yin*. "Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks". The 32nd ACM International Conference on Information and Knowledge Management  (CIKM'23), 21-25 October 2023, Birmingham, UK. (CCF Rank B, CORE Rank A; Corresponding Author)

Jie Liu, Mengting He, Guangtao Wang, Nguyen Quoc Viet Hung, Xuequn Shang, Hongzhi Yin*. "Imbalanced Node Classification Beyond Homophilic Assumption".  The 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 19th-25th August 2023. Macao, S.A.R.

Shangfei Zheng, Hongzhi Yin*, Tong Chen, Quoc Viet Hung Nguyen, Wei Chen, Lei Zhao. "DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning". The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23), Taipei,  23-27 July, 2023. (CCF Rank A, CORE Rank A*; Corresponding Author).

Yu Yang, Hongzhi Yin*, Jiannong Cao, Tong Chen, Quoc Viet Hung Nguyen, Xiaofang Zhou, Lei Chen. "Time-aware Dynamic Graph Embedding for Asynchronous Structural Evolution" .  Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)

Shangfei Zheng, Wei Chen, Weiqing Wang, Pengpeng Zhao, Hongzhi Yin, Lei Zhao. "Multi-Hop Knowledge Graph Reasoning in Few-Shot Scenarios". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (CCF Rank A, CORE Rank A*, Q1 Journal)

Xiangguo Sun, Bo Liu, Jia Li, Hongyang Chen, Guandong Xu, Hongzhi Yin*. "Self-supervised Hypergraph Representation Learning for Sociological Analysis". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (CCF Rank A, CORE Rank A*, Q1 Journal)

Liang Qu, Huaisheng Zhu, Ruiqi Zheng, Yuhui Shi, Hongzhi Yin*. "ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph Networks". The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'21), Singapore. August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author).

Xiangguo Sun, Hongzhi Yin*, Bo Liu, Qing Meng, Jiuxin Cao, Alexander Zhou, and Hongxu Chen. "Structure Learning via Meta-Hyperedge for Dynamic Rumor Detection". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2022. (TKDE'22). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)

Chi Thang Duong, Thanh Tam Nguyen, Trung-Dung Hoang, Hongzhi Yin, Matthias Weidlich, Quoc Viet Hung Nguyen. "Deep MinCut: Learning Node Embeddings from Detecting Communities". Pattern Recognition 2022. (CORE Rank A*, Q1 Journal) 

Cheng Yang, Yuxin Guo, Chuan Shi, Jiawei Liu, Chunchen Wang, Yao Xu, Xin Li, Ning Guo, Hongzhi Yin*. "Learning to Distill Graph Neural Networks". The 16th ACM International WSDM Conference (WSDM'23), Singapore, February 27 to March 3, 2023.

Yufeng Zhang, Weiqing Wang, Hongzhi Yin, Pengpeng Zhao, Wei Chen, Lei Zhao. "Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction". The 39th IEEE International Conference on Data Engineering (ICDE'23), April, 2023. (CCF Rank A, CORE Rank A*)

Shangfei Zheng, Weiqing Wang, Jianfeng Qu, Hongzhi Yin, Wei Chen, Lei Zhao. "MMKGR: Multi-hop Multi-modal Knowledge Graph Reasoning". The 39th IEEE International Conference on Data Engineering (ICDE'23), April, 2023. (CCF Rank A, CORE Rank A*)

Muhammad Imran, Hongzhi Yin*, Tong Chen, Zi Huang, Kai Zheng. "DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks". IEEE Transactions on Knowledge and Data Engineering. 2022. (TKDE'22). (Corresponding author, CCF Rank A, CORE Rank A*, Q1 Journal)

Huynh Thanh Trung, Tong Van Vinh, Nguyen Thanh Tam, Jun Jo, Hongzhi Yin, Quoc Viet Hung Nguyen. "Learning Holistic Interactions in LBSNs with High-order, Dynamic, and Multi-role Contexts". IEEE Transactions on Knowledge and Data Engineering. 2022. (TKDE'22). (CCF Rank A, CORE Rank A*, Q1 Journal)

Chi Thang Duong, Dung Hoang, Hongzhi Yin, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer. "Scalable Robust Graph Embedding with Spark".  The 48th International Conference on Very Large Data Bases (VLDB'22), September 2022. (CCF Rank A; CORE Rank A*)

Muhammad Imran, Hongzhi Yin*, Tong Chen, Zi Huang, Xiangliang Zhang, Kai Zheng. "DDHH: A Decentralized Deep Learning Framework for Large-scale Heterogeneous Networks". IEEE 37th International Conference on Data Engineering (ICDE'21), Greece, April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author).

Mubashir Imran, Hongzhi Yin*, Tong Chen, Yingxia Shao, Xiangliang Zhang and Xiaofang Zhou. "Decentralized Embedding Framework for Large-scale Networks". DASFAA'20, Jeju, South Koren, 2020. (CCF Rank B; Best Student Paper Award, Corresponding author and contributing equally with the first author).

Thanh Trung Huynh, Thang Chi Duong, Thanh Tam Nguyen, Van Vinh Tong, Abdul Sattar, Hongzhi Yin, Quoc Viet Hung Nguyen. "Network Alignment with Holistic Embeddings". IEEE Transactions on Knowledge and Data Engineering. 2021. (TKDE'21). (CCF Rank A, CORE Rank A*, Q1 Journal)

Tong Chen, Hongzhi Yin*, Jie Ren, Zi Huang, Xiangliang Zhang, Hao Wang. "Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning". IEEE Transactions on Knowledge and Data Engineering. 2021. (TKDE'21). (CCF Rank A, CORE Rank A*, Q1 Journal)

Chi Thang Duong, Thanh Tam Nguyen, Hongzhi Yin*, Matthias Weidlich, Thai Son Ma, Karl Aberer, Nguyen Quoc Viet Hung. "Efficient and Effective Multi-Modal Queries through Heterogeneous Network Embedding". IEEE Transactions on Knowledge and Data Engineering. 2021. (TKDE'21). (CCF Rank A, CORE Rank A*,Q1 Journal)

Chi Thang Duong, Dung Hoang, Hongzhi Yin*, Matthias Weidlich, Quoc Viet Hung Nguyen and Karl Aberer. "Efficient Streaming Subgraph Isomorphism with Graph Neural Networks". 47th International Conference on Very Large Data Bases (VLDB'21), August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author).

Hongxu Chen, Hongzhi Yin*, Tong Chen, Quoc Viet Hung Nguyen, Xue Li. "Exploiting Centrality Information with Graph Convolutions for Network Representation Learning". 35th IEEE International Conference on Data Engineering (ICDE'19), Macau SAR. April, 2019. (CCF Rank A, CORE Rank A*, slides).

Qinyong Wang, Hongzhi Yin*, Weiqing Wang, Zi Huang, Guibing Guo and Quoc Viet Hung Nguyen. "Multi-Hop Path Queries over Knowledge Graphs with Neural Memory Networks". The 24th International Conference on Database Systems for Advanced Applications (DASFAA'19), Chiang Mai, Thailand. April, 2019. (CCF Rank B)

Xiangguo Sun, Bo Liu, Hongxu Chen, Wang Han, Qing Meng, Jiuxin Cao and Hongzhi Yin*. "Multi-level Hyperedge Distillation for Social Linking Prediction on Sparsely Observed Networks". The Web Conference 2021 (WWW'21), April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Hongxu Chen, Hongzhi Yin*, Xiangguo Sun, Tong Chen, Bogdan Gabrys and Katarzyna Musial. "Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction". 26th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'20), San Diego, USA. August, 2020. (CCF Rank A, CORE Rank A*, Codes , Corresponding author and supervisor of the first author; Contributing equally with the first author).

Yadan Luo, Zi Huang, Hongxu Chen, Yang Yang, Hongzhi Yin, Mahsa Baktashmotlagh. "Interpretable Signed Link Prediction with Signed Infomax Hyperbolic Graph ". IEEE Transactions on Knowledge and Data Engineering. 2022. (TKDE'22). (CCF Rank A, CORE Rank A*, Q1 Journal)

Junliang Yu, Hongzhi Yin*, Min Gao, Xin Xia, Xiangliang Zhang, Quoc Viet Hung Nguyen. "Socially-Aware Self-Supervised Tri-Training for Recommendation". The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'21), Singapore. August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Sixiao Zhang, Hongxu Chen, Xiao Ming, Lizhen Cui, Hongzhi Yin, Guandong Xu. "Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender Systems".  The 27th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'21), Singapore. August, 2021. (CCF Rank A, CORE Rank A*).

Junliang Yu, Hongzhi Yin*, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung and Xiangliang Zhang. "Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation". The Web Conference 2021 (WWW'21), April, 2021. (CCF Rank A, CORE Rank A*, Codes; Corresponding author and contributing equally with the first author).

Nguyen Thanh Tam, Huynh Thanh Trung, Hongzhi Yin*, Tong Van Vinh, Darnbi Sakong, Bolong Zheng, Nguyen Quoc Viet Hung. "Entity Alignment for Knowledge Graphs with Multi-order Convolutional Networks". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (CCF Rank A, CORE Rank A*, Q1 Journal)

Xiangguo Sun, Hongzhi Yin, Bo Liu, Hongxu Chen, Jiuxin Cao, Yingxia Shao and Nguyen Quoc Viet Hung. "Heterogeneous Hypergraph Embedding for Graph Classification". The 14th ACM International WSDM Conference (WSDM'21), March, 2021. (CCF Rank B, CORE Rank A*; Contributing equally with the first author).

Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li and Hong Chen. "Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation". The 14th ACM International WSDM Conference (WSDM'21), March, 2021. (CCF Rank B, CORE Rank A*).

Thanh Trung Huynh, Van Vinh Tong, Thanh Tam Nguyen, Hongzhi Yin*, Matthias Weidlich and Quoc Viet Hung Nguyen. "Adaptive Network Alignment with Unsupervised and Multi-order Convolutional Networks". 36th IEEE International Conference on Data Engineering(ICDE'2020), Dallas, Texas. April, 2020. (CCF Rank A, CORE Rank A* ).

Hongxu Chen, Hongzhi Yin*, Weiqing Wang, Hao Wang, Quoc Viet Hung Nguyen, Xue Li. "PME: Projected Metric Embedding on Heterogeneous Networks for Link Prediction". 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), London, United Kingdom. August, 2018. (CCF Rank A, CORE Rank A*, Codes Download. The first author is supervised by Dr. Hongzhi Yin).

Hongxu Chen, Hongzhi Yin*, Tong Chen, Weiqing Wang, Xue Li, Xia Hu. "Social Boosted Recommendation with Folded Bipartite Network Embedding". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (Corresponding author and having equal contribution with the first author, CCF Rank A, CORE Rank A*)

Yizhou Sun, Hongzhi Yin, Xiang Ren. "Recommendation in Context-Rich Environment: An Information Network Analysis Approach".WWW '17 Companion, Perth, Australia, April, 2017. (Tutorial, CCF Rank A, CORE Rank A*).

Chi Thang Duong, Hongzhi Yin*, Dung Hoang, Minh Hung Nguyen, Quoc Viet Hung Nguyen, Matthias Weidlich and Karl Aberer. "Graph Embeddings for One-pass Processing of Heterogeneous Queries". 36th IEEE International Conference on Data Engineering(ICDE'2020), Dallas, Texas. April, 2020. (CCF Rank A, CORE Rank A*, short paper).

Xueyan Liu, Bo Yang, Wenzhuo Song, Katarzyna Musial, Wanli Zuo, Hongxu Chen, Hongzhi Yin. "A Block-based Generative Model for Attributed Network Embedding". World Wide Web Journal (WWWJ), 2021. (CCF Rank B, CORE Rank A)

Xiaocui Li, Hongzhi Yin*, Ke Zhou, Xiaofang Zhou. "Semi-supervised Clustering with Deep Metric Learning and Graph Embedding". World Wide Web Journal (WWWJ), 2019. (CCF Rank B, CORE Rank A.)

Saeid Hosseini, Saeed Najafipour, Ngai-Man Cheung, Hongzhi Yin, Mohammad Reza Kangavari, Xiaofang Zhou. "TEAGS: Time-aware Text Embedding Approach to Generate Subgraphs". Data Mining and Knowledge Discovery 2020. (CCF Rank B, CORE Rank A)

Wei Chen, Weiqing Wang, Hongzhi Yin, Lei Zhao, Xiaofang Zhou. "HFUL: A Hybrid Framework for User Account Linkage across Location-Aware Social Networks". The VLDB Journal 2022. (VLDBJ'22). (CCF Rank A, CORE Rank A*, Q1 Journal) 

Li He, Xianzhi Wang, Dingxian Wang, Hanyuan Zou, Hongzhi Yin, Guandong Xu. "Simplifying Graph-based Collaborative Filtering for Recommendation". The 16th ACM International WSDM Conference (WSDM'23), Singapore, February 27 to March 3, 2023.

Xiangguo Sun, Bo Liu, Hongxu Chen, Wang Han, Qing Meng, Jiuxin Cao and Hongzhi Yin*. "Multi-level Hyperedge Distillation for Social Linking Prediction on Sparsely Observed Networks". The Web Conference 2021 (WWW'21), April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Hongxu Chen, Hongzhi Yin*, Xiangguo Sun, Tong Chen, Bogdan Gabrys and Katarzyna Musial. "Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction". 26th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'20), San Diego, USA. August, 2020. (CCF Rank A, CORE Rank A*, Codes , Corresponding author and supervisor of the first author; Contributing equally with the first author).

Nguyen Thanh Tam, Huynh Thanh Trung, Hongzhi Yin*, Tong Van Vinh, Darnbi Sakong, Bolong Zheng, Nguyen Quoc Viet Hung. "Entity Alignment for Knowledge Graphs with Multi-order Convolutional Networks". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (CCF Rank A, CORE Rank A*, Q1 Journal)

Thanh Trung Huynh, Van Vinh Tong, Thanh Tam Nguyen, Hongzhi Yin*, Matthias Weidlich and Quoc Viet Hung Nguyen. "Adaptive Network Alignment with Unsupervised and Multi-order Convolutional Networks". 36th IEEE International Conference on Data Engineering(ICDE'2020), Dallas, Texas. April, 2020. (CCF Rank A, CORE Rank A* ).

Wei Chen, Weiqing Wang, Hongzhi Yin*, Junhua Fang and Lei Zhao. "User Account Linkage across Multiple Platforms with Location Data". Journal of Computer Science and Technology (JCST), 2020. (CCF Rank B).

Wei Chen, Hongzhi Yin*, Weiqing Wang, Lei Zhao and Xiaofang Zhou. "Effective and Efficient User Account Linkage Across Location Based Social Networks". 34th IEEE International Conference on Data Engineering (ICDE'18), Paris, France 2018. (CCF Rank A, CORE Rank A*, Slides Download, Codes Download).

Wei Chen, Hongzhi Yin*,Weiqing Wang, Lei Zhao, Wen Hua and Xiaofang Zhou. "Exploiting Spatio-Temporal User Behaviors for User Linkage". The 25th ACM International Conference on Information and Knowledge Management(CIKM'17), Singapore, November, 2017. (Acceptance Rate:21%, CCF Rank B, CORE Rank A, Slides Download, Codes Download, The first author was supervised by Hongzhi Yin when the work was done at The University of Queensland).

Weiqing Wang, Hongzhi Yin*, Xingzhong Du, Wen Hua, Yongjun Li and Quoc Viet Hung Nguyen. "Online User Representation Learning Across Heterogeneous Social Networks". The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'19), Paris, France. July, 2019. (CCF Rank A, CORE Rank A* ).

Yongjun Li, You Peng, Zhen Zhang, Mingjie Wu, Quanqing Xu, Hongzhi Yin. "A Deep Dive into User Display Names across social networks". Information Science. 2018. (CCF Rank B, CORE Rank A; Impact Factor: 4.832)

Yaqing Wang, Chunyan Feng, Ling Chen, Hongzhi Yin, Caili Guo, Yunfei Chu. "User Identity Linkage across Social Networks via Linked Heterogeneous Network Embedding". World Wide Web Journal (WWWJ), 2018. (CCF Rank B, CORE Rank A.)

Yongjun Li, Zhen Zhang, Quanqing Xu, You Peng, Hongzhi Yin. "Matching User Accounts based on User Generated Content across Social Networks".Future Generation Computer Systems. 2018. (Impact Factor: 4.0, CORE Rank A)

Yongjun Li, You Peng, Zhen Zhang, You Peng, Hongzhi Yin, Quanqing Xu . "Matching user accounts across social network based on username and display name". World Wide Web Journal (WWWJ), 2018. (CCF Rank B, CORE Rank A.)

Yongjun Li, You Peng, Zhen Zhang, Quanqing Xu and Hongzhi Yin. "Understanding the User Display Names across Social Networks".WWW '17 Companion, Perth, Australia, April, 2017.

Yiming Zhou, Yuehui Han, An Liu, Zhixu Li, Hongzhi Yin, Lei Zhao. "Extracting Representative User Subset of Social Networks towards User Characteristics and Topological Features". WISE'18, Dubai, United Arab Emirates, 2018. (CORE Rank A).

Yuting Sun, Tong Chen, Hongzhi Yin*. "Spatial-Temporal Meta-path Guided Explainable Crime Prediction".  World Wide Web 2023. (Corresponding author, CCF Rank B, CORE Rank A, SJR Q1 Journal) 

Yuandong Wang, Hongzhi Yin*, Lian Wu, Tong Chen, Chunyang Liu. "Secure Your Ride: Real-time Matching Success Rate Prediction for Passenger-Driver Pairs". IEEE Transactions on Knowledge and Data Engineering. 2021. (TKDE'21). (Corresponding author; CCF Rank A, CORE Rank A*, Q1 Journal)

Yuandong Wang, Hongzhi Yin*, Tong Chen, Chunyang Liu, Ben Wang, Tianyu Wo, Jie Xu. "Passenger Mobility Prediction via Representation Learning for Dynamic Directed and Weighted Graph". ACM Transaction on Intelligent Systems and Technology. 2021. (TIST'21). (Q1 Journal, 5-year Impact Factor: 10.47; Ranked as one of the best journals in all ACM journals in terms of citations received per paper.)

Yuandong Wang, Hongzhi Yin*, Tong Chen, Chunyang Liu, Ben Wang, Tianyu Wo, Jie Xu. "Gallat: a Spatial-Temporal Graph Attention Network for Passenger Demand Prediction". IEEE 37th International Conference on Data Engineering (ICDE'21), Greece, April, 2021. (CCF Rank A, CORE Rank A*; Corresponding author and contributing equally with the first author).

Yuandong Wang, Hongzhi Yin*, Hongxu Chen, Tianyu Wo, Jie Xu and Kai Zheng. "Origin-Destination Matrix Prediction via Graph Convolution: A New Perspective of Passenger Demand Modeling". 25th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD'19), Anchorage, Alaska, August, 2019. (CCF Rank A, CORE Rank A*, Oral, Acceptance Rate=9%, slides, Codes; Corresponding author and contributing equally with the first author).

Yan Zhao, Kai Zheng, Hongzhi Yin, Guanfeng Liu, Junhua Fang, and Xiaofang Zhou. "Preference-aware Task Assignment in Spatial Crowdsourcing: from Individuals to Groups". IEEE Transactions on Knowledge and Data Engineering. 2020. (TKDE'20). (CCF Rank A, CORE Rank A*)

Zhongjian Lv, Jiajie Xu, Kai Zheng, Pengpeng Zhao, Hongzhi Yin*, Xiaofang Zhou. "LC-RNN: A Deep Learning Model for Traffic Speed Prediction". (IJCAI'18),Stockholm, Sweden 2018. (Corresponding Author, CCF Rank A, CORE Rank A*).

Chongming Gao, Zhong Zhang, Chen Huang, Hongzhi Yin, Qinli Yang, Junming Shao."Semantic Trajectory Representation and Retrieval via Hierarchical Embedding". Information Science 2020. (CCF Rank B, CORE Rank A)

Tieke He, Hongzhi Yin*, Zhenyu Chen, Xiaofang Zhou, Shazia Sadiq, Bin Luo. "A Spatial-Temporal Topic Model for the Semantic Annotation of POIs in LBSNs". ACM Transactions on Intelligent Systems and Technology. 2016. (TIST'16). (5-year Impact Factor: 10.47. The first author was supervised by Hongzhi Yin when he finished the paper.)

Bolong Zheng, Kai Zheng, Xiaokui Xiao, Han Su, Hongzhi Yin, Xiaofang Zhou. "Keyword-Aware Continuous kNN Query on Road Networks". The 32nd IEEE International Conference on Data Engineering (ICDE'16), Helsinki, Finland, May, 2016. (Full research paper, CCF Rank A, CORE Rank A*)

Yanxia Xu, Guanfeng Liu, Hongzhi Yin, Jiajie Xu, Kai Zheng, Lei Zhao. "Discovering Organized POI Groups in a City" . In Proceedings of the 20th International Conference on Database Systems for Advanced Applications (DASFAA). 2015. (CCF Rank B, CORE Rank A)

Mengyu Dou, Tieke He, Hongzhi Yin, Xiaofang Zhou, Bin Luo, Zhenyu Chen. "Predicting Passengers in Public Transportation Using Smart Card Data" . In Proceedings of Australian Database Conference (ADC). 2015.

Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin*. "Unraveling the 'Anomaly' in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution". The 40th IEEE International Conference on Data Engineering (ICDE'24), May 13-16, 2024, Utrecht, Netherlands. (CCF Rank A, CORE Rank A*; Corresponding Author)

Biao Qian, Yang Wang, Hongzhi Yin, Richang Hong, Meng Wang. "Switchable Online Knowledge Distillation". European Conference on Computer Vision (ECCV'22), October, 2022. (CCF Rank B, CORE Rank A*)

Tong Chen, Hongzhi Yin*, Quoc Viet Hung Nguyen, Wen-Chih Peng, Xue Li and Xiaofang Zhou. "Sequence-Aware Factorization Machines for Temporal Predictive Analytics". 36th IEEE International Conference on Data Engineering(ICDE'2020), Dallas, Texas. April, 2020. (CCF Rank A, CORE Rank A* , Corresponding author and supervisor of the first author; Contributing equally with the first author).

Tong Chen, Hongzhi Yin*, Hongxu Chen, Hao Wang, Xiaofang Zhou, Xue Li. "Online Sales Prediction via Trend Alignment based Multi-Task Recurrent Neural Network". Knowledge and Information Systems. 2019. (KAIS'19). (Corresponding author, Q1 Journal, CCF Rank B, Invited ICDM'18 Best Paper)

Hongzhi Yin, Hongxu Chen, Xiaoshuai Sun, Hao Wang, Yang Wang, and Quoc Viet Hung Nguyen. "SPTF: A Scalable Probabilistic Tensor Factorization Model for Semantic-Aware Behavior Prediction". 2017 IEEE International Conference on Data Mining(ICDM'17), New Orleans, USA, November, 2017. (Acceptance Rate:9.5%, Oral, CORE Rank A*, CCF B, Slides Download, Codes Download).

Wensheng Gan, Guoting Chen, Hongzhi Yin, PHILIPPE FOURNIER-VIGER, CHIEN-MING CHEN, PHILIP S. YU. "Towards Revenue Maximization with Popular and Profitable Products". ACM Transactions on Data Science. 2021. (TDS'21).

Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Hongzhi Yin*, Philippe Fournier-Viger, Han-Chieh Chao, and Philip S. Yu. "Utility Mining Across Multi-Dimensional Sequences". ACM Transaction on Knowledge Discovery in Data. 2021. (TKDD'21). (Q1 Journal, CCF Rank B)

Chen Zhang, Hao Wang, Changying Du, Yijun Wang, Can Chen and Hongzhi Yin*. "Reliability Modeling for Stock Comments: A Holistic Perspective". 2018 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), London, United Kingdom. August, 2018. (CCF Rank A, CORE Rank A*. ).

Tong Chen, Hongzhi Yin*, Hongxu Chen, Lin Wu, Hao Wang, Xiaofang Zhou and Xue Li. "TADA: Trend Alignment with Dual-Attention Multi-Task Recurrent Neural Networks for Sales Prediction". 2018 The IEEE International Conference on Data Mining (ICDM'18), Singapore. August 2018. (CCF Rank B, CORE Rank A*, Acceptance Rate=8.86%, Codes Download. This paper has been selected as one of the best papers for possible publication in Knowledge and Information Systems. The first author is supervised by Dr. Hongzhi Yin).

Yu Yang, Zhiyuan Wen, Jiannong Cao, Jiaxing Shen, Hongzhi Yin and Xiaofang Zhou. "EPARS: Early Prediction of At-risk Students with Online and Offline Learning Behaviors". DASFAA'20, Jeju, South Koren, 2020. (CCF Rank B).

Nguyen Quoc Viet Hung, Kai Zheng, Matthias Weidlich, Bolong Zheng, Hongzhi Yin, Nguyen Thanh Tam, Bela Stantic. "What-if Analysis with Conflicting Goals: Recommending Data Ranges for Exploration". 34th IEEE International Conference on Data Engineering (ICDE'18), Paris, France 2018. (CCF Rank A, CORE Rank A*).

Xiaocui Li, Hongzhi Yin*, Ke Li, Hongxu Chen, Shazia Sadiq and Xiaofang Zhou. "Semi-supervised Clustering with Deep Metric Learning". The 24th International Conference on Database Systems for Advanced Applications (DASFAA'19, Short paper), Chiang Mai, Thailand. April, 2019. (CCF Rank B)

Sameen Mansha, Hoang Thanh Lam, Hongzhi Yin, Faisal Kamiran, Mohsen Ali. "Layered Convolutional Dictionary Learning for Sparse Coding Itemset". World Wide Web Journal (WWWJ), 2018. (CCF Rank B, CORE Rank A. The first author is supervised by Dr. Hongzhi Yin)

Chunyang Liu, Ling Chen, Ivor Tsang and Hongzhi Yin. "Towards the Learning of Weighted Multilabel Associative Classifiers". 2018 International Joint Conference on Neural Networks (IJCNN'18), Rio, Brazil. (CORE Rank A).

Thanh Tam Nguyen, Matthias Weidlich, Hongzhi Yin, Bolong Zheng, Quang Huy Nguyen and Quoc Viet Hung Nguyen. "FactCatch: Incremental Pay-as-You-Go Fact Checking with Minimal User Effort". 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR'2020), Xian, China. July, 2020. (CCF Rank A, CORE Rank A* , Corresponding author; Demo Paper).

Phan Thang Cong, Nguyen Thanh Tam, Hongzhi Yin*, Bolong Zheng, Nguyen Quoc Viet Hung, Bela Stantic. "Efficient User Guidance for Validating Participatory Sensing Data". ACM Transaction on Intelligent Systems and Technology. 2019. (TIST'19). ( 5-year Impact Factor: 10.47; Ranked as one of the best journals in all ACM journals in terms of citations received per paper.)

Nguyen Quoc Viet Hung, Huynh Huu Viet, Nguyen Thanh Tam, Matthias Weidlich, Hongzhi Yin, Xiaofang Zhou. "Computing Crowd Consensus with Partial Agreement". IEEE Transaction on Knowledge and Data Engineering. 2018. (TKDE'18). (CCF Rank A,CORE Rank A*)

Nguyen Quoc Viet Hung, Duong Chi Thang, Nguyen Thanh Tam, Matthias Weidlich, Karl Aberer, Hongzhi Yin*, Xiaofang Zhou. "Answer validation for generic crowdsourcing tasks with minimal efforts". VLDB Journal. 2017. (VLDBJ'17). (CCF Rank A,CORE Rank A*)

Nguyen Quoc Viet Hung, Duong Chi Thang, Nguyen Thanh Tam, Matthias Weidlich, Karl Aberer, Hongzhi Yin, Xiaofang Zhou. "Argument Discovery via Crowdsourcing". VLDB Journal. 2017. (VLDBJ'17). (CCF Rank A,CORE Rank A*)

Thanh Tam Nguyen, Matthias Weidlich, Hongzhi Yin, Bolong Zheng, Quoc Viet Hung Nguyen, Bela Stantic. "User Guidance for Efficient Fact Checking". The Forty-fifth International Conference on Very Large Data Bases (VLDB'19), Los Angeles, California. August, 2019. (CCF Rank A, CORE Rank A* ).

Nguyen Thanh Tam, Matthias Weidlich, Bolong Zheng, Hongzhi Yin, Quoc Viet Hung Nguyen, Bela Stantic. "From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms". The Forty-fifth International Conference on Very Large Data Bases (VLDB'19), Los Angeles, California. August, 2019. (CCF Rank A, CORE Rank A* ).

Weiqing Wang, Hongzhi Yin*, Zi Huang, Xiaoshuai Sun and Nguyen Quoc Viet Hung. "Restricted Boltzmann Machine Based Active Learning for Sparse Recommendation". DASFAA'18, Gold Coast, Australia, 2018. (CCF Rank B, Slides Download).

Xiangguo Sun, Bo Liu, Jia Li, Hongyang Chen, Guandong Xu, Hongzhi Yin*. "Self-supervised Hypergraph Representation Learning for Sociological Analysis". Accepted by IEEE Transactions on Knowledge and Data Engineering. 2023. (TKDE'23). (CCF Rank A, CORE Rank A*, Q1 Journal)

Thanh Tam Nguyen, Zhao Ren, Thanh Toan Nguyen, Jun Jo, Quoc Viet Hung Nguyen, Hongzhi Yin. "Portable Graph-based Rumour Detection against Multi-modal Heterophily". Knowledge-Based Systems 2024. (KBS, Q1 Journal) 

Thanh Cong Phan, Thanh Tam Nguyen, Matthias Weidlich, Hongzhi Yin, Jun Jo, Quoc Viet Hung Nguyen. "exRumourLens: Auditable Rumour Detection with Multi-View Explanations" . The 38th  IEEE International Conference on Data Engineering (ICDE'22), May 2022. (Demo, CORE Rank A*, CCF Rank A) 

Thanh Tam Nguyen, Thanh Cong Phan, Matthias Weidlich, Hongzhi Yin, Jun Jo and Quoc Viet Hung Nguyen. "Model-Agnostic and Diverse Explanations for Streaming Rumour Graphs" . Knowledge-Based Systems. 2022. (KBS'22).(Q1 Journal) 

Hongzhi Yin*, Zhiting Hu, Xiaofang Zhou, Hao Wang, Kai Zheng, Quoc Viet Hung Nguyen. "Discovering Interpretable Geo-Social Communities for User Behavior Prediction". The 32nd IEEE International Conference on Data Engineering (ICDE'16), Helsinki, Finland, May, 2016. (Full research paper, CCF Rank A, CORE Rank A*, Slides Download, Codes(PWD:nm0t)).

Nguyen Quoc Viet Hung, Duong Chi Thang, Nguyen Thanh Tam, Matthias Weidlich, Karl Aberer, Hongzhi Yin, Xiaofang Zhou. "Argument Discovery via Crowdsourcing". VLDB Journal. 2017. (VLDBJ'17). (CCF Rank A,CORE Rank A*)

Nguyen Thanh Tam, Matthias Weidlich, Bolong Zheng, Hongzhi Yin, Quoc Viet Hung Nguyen, Bela Stantic. "From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms". The Forty-fifth International Conference on Very Large Data Bases (VLDB'19), Los Angeles, California. August, 2019. (CCF Rank A, CORE Rank A* ).

Yanling Wang, Jing Zhang, Shasha Guo, Hongzhi Yin, Cuiping Li and Hong Chen. "Decoupling Representation Learning and Classification for GNN-based Anomaly Detection". The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), July, 2021. (CCF Rank A, CORE Rank A*).

Yiming Zhou, Yuehui Han, An Liu, Zhixu Li, Hongzhi Yin, Wei Chen, Lei Zhao. "Extracting representative user subset of social networks towards user characteristics and topological features". World Wide Web 2020. (CCF Rank B, CORE Rank A)

Xiangguo Sun, Bo Liu, Qing Meng, Jiuxin Cao, Junzhou Luo, Hongzhi Yin. "Group-level Personality Detection based on Text Generated Networks". World Wide Web Journal (WWWJ), 2019. (CCF Rank B, CORE Rank A.)

Tong Chen, Xue Li, Hongzhi Yin*, Jun Zhang. "Call Attention to Rumors: Deep Attention Based Recurrent Neural Networks for Early Rumor Detection". Workshop of PAKDD'18 on The Big Data Analytics for Social Computing, Melbourne, Australia, 2018. (Best Paper Award)

Yiran Xie, Hongzhi Yin, Bin Cui, Junjie Yao, Quanqing Xu. "Distinguishing re-sharing behaviors from re-creating behaviors in information diffusion " . World Wide Web Journal (WWWJ), 2016. (CCF Rank B, CORE Rank A.)

Hongxu Chen, Hongzhi Yin, Meng Wang, Weitong Chen, Tong Chen and Xue Li. "People Opinion Topic Model: Opinion based User Clustering in Social Networks". WWW '17 Companion, Perth, Australia, April, 2017.

Hongzhi Yin*, Bin Cui, Hua Lu, Yuxin Huang, Junjie Yao. "A Unified Model for Stable and Temporal Topic Detection from Social Media Data". Proc. of 2013 IEEE Int. Conf. on Data Engineering (ICDE’13), Brisbane, Australia, Apr. 2013. (Full research paper, Acceptance rate: 19%, CCF Rank A, CORE Rank A*, Slides, Code Download)

Hao Wang, Chen Zhang, Hongzhi Yin, Wei Wang, Jun Zhang, Fanjiang Xu. "A Unified Framework for Fine-Grained Opinion Mining from Online Reviews ". The 49th Hawaii International Conference on System Sciences (HICSS'16), Hawaii, January, 2016. (Full research paper, CORE Rank A)

Meng Zhao, Hao Wang, Liangliang Cao, Chen Zhang, Hongzhi Yin, Fanjiang Xu. "LSIF: A System for Large-scale Information Flow Detection Based on Topic-related Semantic Similarity Measurement ". The 2015 IEEE/WIC/ACM International Conference on Web Intelligence(WI'15), Singapore, December, 2015. (Full research paper, CORE Rank B)

Yiran Xie, Hongzhi Yin, Bin Cui, Junjie Yao, Quanqing Xu. "Distinguishing Re-sharing Behaviors from Re-creating Behaviors in Information Diffusion" . ICDE 2015 Workshop (SSEPM 2015).

Ruihong Qiu, Sen Wang, Zhi Chen, Hongzhi Yin, Zi Huang. "CausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation".   The 29th ACM International Conference on Multimedia (MM'21), 2021.  (CCF Rank A, CORE Rank A*)

Xingdong Du, Hongzhi Yin*, Ling Chen, Yang Wang, Yi Yang, Xiaofang Zhou. "Personalized Video Recommendation Using Rich Contents from Videos". IEEE Transaction on Knowledge and Data Engineering. 2019. (TKDE'19). (Corresponding author,CCF Rank A,CORE Rank A*, Code Download)

Lin Wu, Yang Wang, Hongzhi Yin, Meng Wang, Ling Shao. "Few-Shot Deep Adversarial Learning for Video-based Person Re-identification". IEEE Transactions on Image Processing. 2020. (TIP'20). (CCF Rank A, CORE Rank A*)

Hongzhi Yin*, Weiqing Wang, Liang Chen, Xingzhong Du, Nguyen Quoc Viet Hung, Zi Huang. "Mobi-SAGE-RS: A Sparse Additive Generative Model-based Mobile Application Recommender System". Knowledge-Based Systems. 2018. (KBS'18).(Q1 Journal; Impact Factor: 4.6. )

Hongzhi Yin,Liang Chen, Weiqing Wang, Xingzhong Du, Quoc Viet Hung Nguyen and Xiaofang Zhou. "Mobi-SAGE: A Sparse Additive Generative Model for Mobile App Recommendation". 2017 IEEE International Conference on Data Engineering(ICDE'17), San Diego, California, April, 2017. (Short Paper, CCF Rank A, CORE Rank A*).

Ziwei Wang, Yadan Luo, Yang Li, Zi Huang, Hongzhi Yin. "Look Deeper See Richer: Depth-aware Image Paragraph Captioning". ACM Multimedia 2018 (MM'18), Seoul, Korea, October 2018. (CCF Rank A, CORE Rank A*. The first author is co-supervised by Dr. Hongzhi Yin).

Xingzhong Du, Hongzhi Yin*, Zi Huang, Yi Yang, Xiaofang Zhou. "Exploiting Detected Visual Objects for Frame-level Video Filtering". World Wide Web Journal (WWWJ), Accepted in October, 2017. (CCF Rank B, CORE Rank A. The first author is supervised by Dr. Hongzhi Yin)

Xiaoshuai Sun, Zi Huang, Hongzhi Yin, Hengtao Shen. "An Integrated Model for Effective Saliency Prediction".The Thirty-First AAAI Conference on Artificial Intelligence(AAAI'17), San Francisco, California, USA, February, 2017. (Full research paper, CCF Rank A, CORE Rank A*).

Xingzhong Du, Hongzhi Yin, Zi Huang, Yi Yang, Xiaofang Zhou. "Using Detected Visual Objects to Index Video Database ". The 2016 Australian Database Conference (ADC'16), Sydney, Australia, 2016. (Best Paper,Full research paper)

Chi Thang Duong, Dung Hoang, Hongzhi Yin*, Matthias Weidlich, Quoc Viet Hung Nguyen and Karl Aberer. "Efficient Streaming Subgraph Isomorphism with Graph Neural Networks". 47th International Conference on Very Large Data Bases (VLDB'21), August, 2021. (CCF Rank A, CORE Rank A*; Corresponding author).

Jinjing Huang, Wei Chen, An Liu, Weiqing Wang, Hongzhi Yin, Lei Zhao. "Cluster query: a new query pattern on temporal knowledge graph". World Wide Web 2020. (CCF Rank B, CORE Rank A)

Jinjing Huang, Wei Chen, Zhixu Li, Pengpeng Zhao, Weiqing Wang, Hongzhi Yin, Lei Zhao. "SGPM: a privacy protected approach of time-constrained graph pattern matching in cloud". World Wide Web 2020. (CCF Rank B, CORE Rank A)

Jiuru Gao, Wei Chen, Jiajie Xu, An Liu, Zhixu Li, Hongzhi Yin, Lei Zhao. "An Efficient Framework for Multiple Subgraph Pattern Matching Models". Journal of Computer Science and Technology . 2019. (JCST'19, CCF Rank B).

Saeid Hosseini, Hongzhi Yin*, Ngai-Man Cheung, Kan Pak Leng, Yuval Elovici and Xiaofang Zhou. "Exploiting Reshaping Subgraphs From Bilateral Propagation Graphs". DASFAA'18, Gold Coast, Australia, 2018. (CCF Rank B, Short Paper).

Jiuru Gao, Jiajie Xu, Guanfeng Liu, Wei Chen, Hongzhi Yin and Lei Zhao. "A Privacy-Preserving Framework for Subgraph Pattern Matching in Cloud". DASFAA'18, Gold Coast, Australia, 2018. (CCF Rank B).

Qing Qian, Zhixu Li, Pengpeng Zhao, Wei Chen, Hongzhi Yin and Lei Zhao. "Publishing Graph Node Strength Histogram with Edge Differential Privacy". DASFAA'18, Gold Coast, Australia, 2018. (CCF Rank B).

Lingjiao Lu, Junhua Fang, Pengpeng Zhao, Jiajie Xu, Hongzhi Yin, Lei Zhao. "Eliminating Temporal Conflicts in Uncertain Temporal Knowledge Graphs". WISE'18, Dubai, United Arab Emirates, 2018. (CORE Rank A).

Saeid Hosseini, Hongzhi Yin*, Meihui Zhang, Yuval Elovici, Xiaofang Zhou. "Mining Subgraphs From Propagation Networks Through Temporal Dynamic Analysis". MDM'18, Aalborg, Demark, 2018. (CCF Rank C).

Jinjing Huang, Tianqiao Lin, An Liu, Zhixu Li, Hongzhi Yin, Lei Zhao. "Influenced Nodes Discovery in Temporal Contact Network".(WISE'17), Puschino, Russia, 2017. (Full research paper, CCF Rank C, CORE Rank A).

Yanxia Xu, Jinjing Huang, An Liu, Zhixu Li, Hongzhi Yin, Lei Zhao. "Time-Constrained Graph Pattern Matching in a Large Temporal Graph" . APWEB-WAIM 2017, Beijing, China, 2017. (Full research paper, CORE Rank B, CCF Rank C)