Associate Professor Hongzhi Yin

ARC Future Fellow

School of Electrical Engineering and Computer Science

+61 7 336 54739

h.yin1@uq.edu.au

Researcher biography

Prof. Hongzhi Yin works as an ARC Future Fellow and Professor and director of the Responsible Big Data Intelligence Lab (RBDI) at The University of Queensland, Australia. He has made notable contributions to predictive analytics, recommendation systems, graph learning, social media analytics, and decentralized and edge intelligence. He has received numerous awards and recognition for his research achievements. He has been named to IEEE Computer Society's AI's 10 to Watch 2022 and Field Leader of Data Mining & Analysis in The Australian's Research 2020 magazine. In addition, he has received the prestigious 2023 Young Tall Poppy Science Awards, Australian Research Council Future Fellowship 2021, the Discovery Early Career Researcher Award 2016, UQ Foundation Research Excellence Award 2019, Rising Star of Science Award (2023 and 2022), AI 2000 Most Influential Scholar Honorable Mention in Data Mining (2023 and 2022). His research has won 8 international and national Best Paper Awards, including Best Paper Award - Honorable Mention at WSDM 2023, Best Paper Award at ICDE 2019, Best Student Paper Award at DASFAA 2020, Best Paper Award Nomination at ICDM 2018, ACM Computing Reviews' 21 Annual Best of Computing Notable Books and Articles, Best Paper Award at ADC 2018 and 2016. His Ph.D. thesis won Peking University Outstanding Ph.D. Dissertation Award 2014 and CCF Outstanding Ph.D. Dissertation Award (Nomination) 2014. He has ten conference papers recognized as the Most Influential Papers in KDD 2021 and 2013, AAAI 2021, SIGIR 2022, WWW 2023 and 2021, CIKM 2021, 2019, 2016, and 2015. He has published 280+ papers with an H-index of 67, including 170+ CCF A and 70+ CCF B, 170+ CORE A* and 70+ CORE A, such as KDD, SIGIR, WWW, WSDM, SIGMOD, VLDB, ICDE, AAAI, IJCAI, ACM Multimedia, ECCV, IEEE TKDE, TNNL, VLDB Journal, and ACM TOIS. He has been the leading author (first/co-first author or corresponding author) for 180+. He has been an SPC/PC member for many top conferences, such as AAAI, IJCAI, KDD, ICML, ICLR, NeurIPS, SIGIR, WWW, WSDM, VLDB, ICDE, ICDM, and CIKM. He is currently serving as Associate Editor/Guest Editor/Editorial Board for ACM Transactions on Information Systems (TOIS), ACM Transactions on Intelligent Systems and Technology (TIST), Information Systems, and World Wide Web, Journal of Computer Science and Technology (JCST), Big Data Networks (specialty section of Frontiers in ICT, Frontiers in Digital Humanities, Frontiers in Big Data and Frontiers in Computer Science), Springer Nature Computer Science, Information, and International Journal of Software and Informatics (IJSI). Dr. Yin has also been attracting wide media coverage, such as The Australian, Edge Impulse, SBS Radio Interviews, UQ News, Sohu.com, Faculty News of EAIT, IEEE Computer Society, ACM Computing Reviews.

Dr. Hongzhi Yin is looking for highly motivated and high-quality Ph.D. students. The University of Queensland ranks in the top 50 as measured by the Performance Ranking of Scientific Papers for World Universities. The University also ranks 47 in the QS World University Rankings, 52 in the US News Best Global Universities Rankings, 60 in the Times Higher Education World University Rankings, and 55 in the Academic Ranking of World Universities.

Latest News

[1 December 2023] We have four research papers accepted by the top conference ICDE 2024 1st Round (CORE A*, CCF A).
- Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation
- Graph Condensation for Inductive Node Representation Learning
- BOURNE: Bootstrapped Self-supervised Learning Framework for Unified Graph Anomaly Detection
- HeteFedRec: Federated Recommender Systems with Model Heterogeneity
[30 October 2023] Our ARC DP 2024 application, titled "Privacy-Aware and Personalised Explanation Overlays for Recommender Systems", has been granted and funded.
[20 October 2023] We have three research papers accepted as ORAL by the top conference WSDM 2024.
- Budgeted Embedding Table For Recommender Systems
- Defense Against Model Extraction Attacks on Recommender Systems
- Motif-based Prompt Learning for Universal Cross-domain Recommendation
[17 October 2023] Our research paper "Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation" has been accepted by the top conference ICDE 2024 (CORE A* and CCF A).
[16 October 2023] Our research paper "Manipulating Visually-aware Federated Recommender Systems and Its Countermeasures" has been accepted by the top journal TOIS (CORE A and CCF A).
[1 October 2023] Our research paper "Variational Counterfactual Prediction under Runtime Domain Corruption" has been accepted by the top journal TKDE 2023 (CORE A* and CCF A).
[6 September 2023] I was invited to serve as Senior PC for PAKDD 2024 and DASFAA 2024.
[6 September 2023] We have two papers accepted by the top conference ICDM 2023 (Acceptance Rate 9.73% for Regular Papers).
- Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation
- To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data
[6 August 2023] I have been recognized as one of 2023 Young Tall Poppy Science Award winners.
[5 August 2023] We have four research papers accepted by the top conference CIKM 2023.
- Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation
- Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks
- Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph
- Causality-guided Graph Learning for Session-based Recommendation
[24 July 2023] I was invited to serve as an Area Chair (AC) for the User Modeling and Recommendation track of The Web Conference 2024.
[24 July 2023] We have two TKDE papers recognized as ESI Highly Cited Papers.
- Enhancing Social Recommendation With Adversarial Graph Convolutional Networks - TKDE 2022.
- Preference-Aware Task Assignment in Spatial Crowdsourcing: From Individuals to Groups - TKDE 2022.
[12 July 2023] Our research paper "Comprehensive Privacy Analysis on Federated Recommender System against Attribute Inference Attacks" has been accepted by the top journal TKDE 2023 (CORE A* and CCF A).
[22 June 2023] Congratulations to my Ph.D. graduates Dr. Shijie Zhang and Dr. Qinyong Wang on winning UQ Graduate School 2022 and 2021 Dean's Award for Outstanding Higher Degree by Research Theses.
[20 June 2023] Congratulations to my Ph.D. student Dr. Junliang Yu on achieving his Ph.D. from The University of Queensland.
[19 June 2023] Our research paper "XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation" has been accepted by the top journal TKDE 2023 (CORE A* and CCF A).
[2 June 2023] Our research paper "Self-Supervised Learning for Recommender Systems: A Survey" has been accepted by the top journal TKDE 2023 (CORE A* and CCF A).
[18 May 2023] I was invited to be an SPC for the top conference CIKM 2023.
[17 May 2023] Our research paper "Efficient Bi-Level Optimization for Recommendation Denoising" was accepted by the top conference KDD 2023 Research Track (CORE A* and CCF A).
[4 May 2023] I am excited to receive the prestigious "AI's 10 to Watch" award from the IEEE Computer Society, IEEE Intelligent Systems.
[2 May 2023] Our research paper "KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment" was accepted by the top conference ACL 2023 (CCF A and CORE A*). Congratulations to Lingzhi!
[20 April 2023] Our research paper "Imbalanced Node Classification Beyond Homophilic Assumption" was accepted by the top conference IJCAI 2023 (CCF A and CORE A*). Congratulations to Jie Liu!
[10 April 2023] I was invited to give a speech on the public webinar "Application and Future Challenges of ChatGPT " by the editorial office of Human-Centric Intelligent Systems.
[6 April 2023] We have four full research papers accepted by the top conference SIGIR 2023 (CCF A and CORE A*) . Congratulations to the Ph.D. students Wei Yuan, Jing Long, Yunke Qu, and Shangfei Zheng.
- Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures
- Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation
- Continuous Input Embedding Size Search For Recommender Systems
- DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning
[8 March 2023] Our research paper "TinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT" has been accepted by the highly impacted journal - IEEE Transactions on Industrial Informatics (JCR Q1). Congratulations to Yuting.
[2 March 2023] Our research paper "Knowledge Enhancement for Contrastive Multi-Behavior Recommendation" has won "Best Paper Award - Honorable Mention" at WSDM 2023.
[1 March 2023] We organize a special issue on Graph Representation Learning for Feature Extraction and Signal Processing in CAAI Transactions on Intelligence Technology (JCR Q1), calling for papers.
[18 Feb 2023] Our research work "Heterogeneous Collaborative Learning for Personalized Healthcare Analytics via Messenger Distillation" was accepted by IEEE Journal of Biomedical and Health Informatics (JBHI) 2023 (CORE A* and Q1). Congratulations to Guanhua.
[15 Feb 2023] Our research work "Time-aware Dynamic Graph Embedding for Asynchronous Structural Evolution" was accepted by TKDE 2023 (CORE A* and CCF A).
[27 January 2023] I was invited to join the Doctoral Consortium Committee of WSDM 2023 as a Mentor.
[26 January 2023] We have 2 research papers accepted by The Web Conference 2023 (CCF A and CORE A*). Congratulations to the first authors Wei Yuan and Liang Qu.
- Interaction-level Membership Inference Attack Against Federated Recommender Systems
- Semi-decentralized Federated Ego Graph Learning for Recommendation
[9 January 2023] Our research paper "Knowledge Enhancement for Contrastive Multi-Behavior Recommendation" has been shortlisted for the Best Paper Award (BPA) for WSDM 2023, and there are only four BPA candidate papers.
[6 January 2023] Our research paper "Efficient On-Device Session-Based Recommendation" was accepted by the top journal ACM Transactions on Information Systems (TOIS, CCF A, CORE A).
[3 January 2023] Our social computing work "Self-supervised Hypergraph Representation Learning for Sociological Analysis" was accepted by the top journal TKDE (CORE A* and CCF A).

Publications

Book (1)

Book Chapters (2)

Journal Articles (111)

Conference Papers (168)

Book

Yin, Hongzhi and Cui, Bin (2016). Spatio-temporal recommendation in social media. Singapore: Springer Singapore. doi: 10.1007/978-981-10-0748-4

Book Chapters

Wang, Weiqing and Yin, Hongzhi (2019). Spatiotemporal recommendation with big geo-social networking data. Big data recommender systems - Volume 1: Algorithms, architectures, big data, security and trust. (pp. 193-224) edited by Osman Khalid, Samee U. Khan and Albert Y. Zomaya. Stevenage, United Kingdom: The Institution of Engineering and Technology. doi: 10.1049/pbpc035f_ch9

Yin, Hongzhi, Cui, Bin and Zhou, Xiaofang (2018). Spatiotemporal recommendation in geo-social networks. Encyclopedia of Social Network Analysis and Mining. (pp. 2930-2948) edited by Reda Alhajj and Jon Rokne. New York, NY, United States: Springer New York. doi: 10.1007/978-1-4939-7131-2_110177

Journal Articles

Sun, Xiangguo, Cheng, Hong, Liu, Bo, Li, Jia, Chen, Hongyang, Xu, Guandong and Yin, Hongzhi (2023). Self-supervised hypergraph representation learning for sociological analysis. IEEE Transactions on Knowledge and Data Engineering, 35 (11), 11860-11871. doi: 10.1109/tkde.2023.3235312

Ye, Guanhua, Chen, Tong, Li, Yawen, Cui, Lizhen, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2023). Heterogeneous collaborative learning for personalized healthcare analytics via messenger distillation. IEEE Journal of Biomedical and Health Informatics, 27 (11), 5249-5259. doi: 10.1109/jbhi.2023.3247463

Yuan, Wei, Yuan, Shilong, Yang, Chaoqun, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2023). Manipulating Visually-aware Federated Recommender Systems and Its Countermeasures. ACM Transactions on Information Systems. doi: 10.1145/3630005

Xia, Xin, Yu, Junliang, Wang, Qinyong, Yang, Chaoqun, Hung, Nguyen Quoc Viet and Yin, Hongzhi (2023). Efficient on-device session-based recommendation. ACM Transactions on Information Systems, 41 (4) 102, 1-24. doi: 10.1145/3580364

Nguyen, Thanh Toan, Huynh, Thanh Trung, Weidlich, Matthias, Tho, Quan Thanh, Yin, Hongzhi, Aberer, Karl and Nguyen, Quoc Viet Hung (2023). Scalable maximal subgraph mining with backbone-preserving graph convolutions. Information Sciences, 644 119287, 119287. doi: 10.1016/j.ins.2023.119287

Sun, Xiangguo, Yin, Hongzhi, Liu, Bo, Meng, Qing, Cao, Jiuxin, Zhou, Alexander and Chen, Hongxu (2023). Structure learning via meta-hyperedge for dynamic rumor detection. IEEE Transactions on Knowledge and Data Engineering, 35 (9), 9128-9139. doi: 10.1109/tkde.2022.3221438

Yin, Hongzhi, Sun, Yizhou, Xu, Guandong and Kanoulas, Evangelos (2023). Trustworthy Recommendation and Search: Introduction to the Special Section - Part 2. ACM Transactions on Information Systems, 41 (4) 82, 1-6. doi: 10.1145/3604776

Sun, Yuting, Chen, Tong and Yin, Hongzhi (2023). Spatial-temporal meta-path guided explainable crime prediction. World Wide Web, 26 (4), 2237-2263. doi: 10.1007/s11280-023-01137-3

Guo, Lei, Zhang, Jinyu, Chen, Tong, Wang, Xinhua and Yin, Hongzhi (2023). Reinforcement learning-enhanced shared-account cross-domain sequential recommendation. IEEE Transactions on Knowledge and Data Engineering, 35 (7), 7397-7411. doi: 10.1109/tkde.2022.3185101

Yu, Junliang, Xia, Xin, Chen, Tong, Cui, Lizhen, Hung, Nguyen Quoc Viet and Yin, Hongzhi (2023). XSimGCL: towards extremely simple graph contrastive learning for recommendation. IEEE Transactions on Knowledge and Data Engineering, 1-14. doi: 10.1109/tkde.2023.3288135

Yu, Junliang, Yin, Hongzhi, Xia, Xin, Chen, Tong, Li, Jundong and Huang, Zi (2023). Self-supervised learning for recommender systems: a survey. IEEE Transactions on Knowledge and Data Engineering, 1-20. doi: 10.1109/tkde.2023.3282907

Wang, Shiqi, Gao, Chongming, Gao, Min, Yu, Junliang, Wang, Zongwei and Yin, Hongzhi (2023). Who are the best adopters? User selection model for free trial item promotion. IEEE Transactions on Big Data, 9 (2), 746-757. doi: 10.1109/tbdata.2022.3205334

Zheng, Ruiqi, Qu, Liang, Cui, Bin, Shi, Yuhui and Yin, Hongzhi (2023). AutoML for deep recommender systems: a survey. ACM Transactions on Information Systems, 41 (4) 101, 1-38. doi: 10.1145/3579355

Gao, Xinyi, Pan, Zhibin, Fan, Guojun, Zhang, Xiaoran and Yin, Hongzhi (2023). Local feature-based mutual complexity for pixel-value-ordering reversible data hiding. Signal Processing, 204 108833, 1-15. doi: 10.1016/j.sigpro.2022.108833

Yang, Yu, Yin, Hongzhi, Cao, Jiannong, Chen, Tong, Nguyen, Quoc Viet Hung, Zhou, Xiaofang and Chen, Lei (2023). Time-Aware Dynamic Graph Embedding for Asynchronous Structural Evolution. IEEE Transactions on Knowledge and Data Engineering, 35 (9), 1-14. doi: 10.1109/tkde.2023.3246059

Yin, Hongzhi, Sun, Yizhou, Xu, Guandong and Kanoulas, Evangelos (2023). Trustworthy Recommendation and Search: Introduction to the Special Issue - Part 1. ACM Transactions on Information Systems, 41 (3) 51, 1-5. doi: 10.1145/3579995

Imran, Mubashir, Yin, Hongzhi, Chen, Tong, Hung, Nguyen Quoc Viet, Zhou, Alexander and Zheng, Kai (2023). ReFRS: Resource-efficient Federated Recommender System for dynamic and diversified user preferences. ACM Transactions on Information Systems, 41 (3) 65, 65:1-65:30 . doi: 10.1145/3560486

Long, Jing, Chen, Tong, Hung, Nguyen Quoc Viet and Yin, Hongzhi (2023). Decentralized collaborative learning framework for next POI recommendation. ACM Transactions on Information Systems, 41 (3) 66, 66:1-66:25. doi: 10.1145/3555374

Duong, Chi Thang, Nguyen, Thanh Tam, Hoang, Trung-Dung, Yin, Hongzhi, Weidlich, Matthias and Nguyen, Quoc Viet Hung (2023). Deep MinCut: learning node embeddings by detecting communities. Pattern Recognition, 134 109126, 1-11. doi: 10.1016/j.patcog.2022.109126

Hao, Bowen, Yin, Hongzhi, Zhang, Jing, Li, Cuiping and Chen, Hong (2023). A multi-strategy based pre-training method for cold-start recommendation. ACM Transactions on Information Systems, 41 (2) 31, 1-24. doi: 10.1145/3544107

Zhang, Peng-Fei, Bai, Guangdong, Yin, Hongzhi and Huang, Zi (2023). Proactive privacy-preserving learning for cross-modal retrieval. ACM Transactions on Information Systems, 41 (2), 1-23. doi: 10.1145/3545799

Wang, Xin, Sapino, Maria Luisa, Han, Wook-Shin, Shao, Yingxiao and Yin, Hongzhi (2023). Special Issue of DASFAA 2023. Data Science and Engineering, 8 (3), 1-2. doi: 10.1007/s41019-023-00231-w

Zhang, Shijie, Yuan, Wei and Yin, Hongzhi (2023). Comprehensive privacy analysis on federated recommender system against attribute inference attacks. IEEE Transactions on Knowledge and Data Engineering. doi: 10.1109/tkde.2023.3295601

Sun, Yuting, Chen, Tong, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2023). TinyAD: memory-efficient anomaly detection for time series data in industrial IoT. IEEE Transactions on Industrial Informatics. doi: 10.1109/tii.2023.3254668

Wen, Hechuan, Chen, Tong, Chai, Li Kheng, Sadiq, Shazia, Gao, Junbin and Yin, Hongzhi (2023). Variational Counterfactual Prediction under Runtime Domain Corruption. IEEE Transactions on Knowledge and Data Engineering, 1-14. doi: 10.1109/tkde.2023.3321893

Bai, Feifei, Cui, Yi, Yan, Ruifeng, Yin, Hongzhi, Chen, Tong, Dart, David and Yaghoobi, Jalil (2023). Cost-effective synchrophasor data source authentication based on multiscale adaptive coupling correlation detrended analysis. International Journal of Electrical Power and Energy Systems, 144 108606, 108606. doi: 10.1016/j.ijepes.2022.108606

Hao, Bowen, Yin, Hongzhi, Li, Cuiping and Chen, Hong (2022). Self-supervised graph learning for occasional group recommendation. International Journal of Intelligent Systems, 37 (12), 10880-10902. doi: 10.1002/int.23011

Nguyen, Thanh Tam, Phan, Thanh Cong, Nguyen, Minh Hieu, Weidlich, Matthias, Yin, Hongzhi, Jo, Jun and Nguyen, Quoc Viet Hung (2022). Model-agnostic and diverse explanations for streaming rumour graphs. Knowledge-Based Systems, 253 109438, 1-15. doi: 10.1016/j.knosys.2022.109438

Cui, Yi, Bai, Feifei, Yin, Hongzhi, Chen, Tong, Dart, David, Zillmann, Matthew and Ko, Ryan K. L. (2022). Multiscale adaptive multifractal detrended fluctuation analysis-based source identification of synchrophasor data. IEEE Transactions on Smart Grid, 13 (6), 1-4. doi: 10.1109/tsg.2022.3207066

Nguyen, Thanh Tam, Huynh, Thanh Trung, Yin, Hongzhi, Weidlich, Matthias, Nguyen, Thanh Thi, Mai, Thai Son and Nguyen, Quoc Viet Hung (2022). Detecting rumours with latency guarantees using massive streaming data. VLDB Journal, 32 (2), 1-19. doi: 10.1007/s00778-022-00750-4

Cui, Yue, Sun, Hao, Zhao, Yan, Yin, Hongzhi and Zheng, Kai (2022). Sequential-knowledge-aware next POI recommendation: a meta-learning approach. ACM Transactions on Information Systems, 40 (2) 3460198, 1-22. doi: 10.1145/3460198

Zhang, Chengyuan, Wang, Yang, Zhu, Lei, Song, Jiayu and Yin, Hongzhi (2022). Multi-graph heterogeneous interaction fusion for social recommendation. ACM Transactions on Information Systems, 40 (2) 3466641, 1-26. doi: 10.1145/3466641

Qiu, Ruihong, Huang, Zi, Chen, Tong and Yin, Hongzhi (2022). Exploiting positional information for session-based recommendation. ACM Transactions on Information Systems, 40 (2) 3473339, 1-24. doi: 10.1145/3473339

Chen, Wei, Wang, Weiqing, Yin, Hongzhi, Zhao, Lei and Zhou, Xiaofang (2022). HFUL: a hybrid framework for user account linkage across location-aware social networks. VLDB Journal, 32 (1), 1-22. doi: 10.1007/s00778-022-00730-8

Li, Kaili, Duan, Haoran, Liu, Linfeng, Qiu, Ruihong, van den Akker, Ben, Ni, Bing-Jie, Chen, Tong, Yin, Hongzhi, Yuan, Zhiguo and Ye, Liu (2022). An integrated first principal and deep learning approach for modeling nitrous oxide emissions from wastewater treatment plants. Environmental Science and Technology, 56 (4) acs.est.1c05020, 2816-2826. doi: 10.1021/acs.est.1c05020

Zheng, Kai, Li, Yong, Shahabi, Cyrus and Yin, Hongzhi (2022). Introduction to the Special Issue on Intelligent Trajectory Analytics: Part I. ACM Transactions on Intelligent Systems and Technology, 13 (1) 1, 1-2. doi: 10.1145/3495230

Wang, Yuandong, Yin, Hongzhi, Chen, Tong, Liu, Chunyang, Wang, Ben, Wo, Tianyu and Xu, Jie (2022). Passenger mobility prediction via representation learning for dynamic directed and weighted graphs. ACM Transactions on Intelligent Systems and Technology, 13 (1) 2, 1-25. doi: 10.1145/3446344

Guo, Lei, Yin, Hongzhi, Chen, Tong, Zhang, Xiangliang and Zheng, Kai (2022). Hierarchical hyperedge embedding-based representation learning for group recommendation. ACM Transactions on Information Systems, 40 (1) 3, 1-27. doi: 10.1145/3457949

Aberer, Karl, Katakis, Ioannis, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2022). Preface - Special Issue on Misinformation on the Web. Information Systems, 103 101867, 101867. doi: 10.1016/j.is.2021.101867

Huynh, Thanh Trung, Tong, Vinh Van, Nguyen, Thanh Tam, Jo, Jun, Yin, Hongzhi and Nguyen, Quoc Viet Hung (2022). Learning holistic interactions in LBSNs with high-order, dynamic, and multi-role contexts. IEEE Transactions on Knowledge & Data Engineering, PP (99), 1-1. doi: 10.1109/TKDE.2022.3150792

Imran, Mubashir, Yin, Hongzhi, Chen, Tong, Huang, Zi and Zheng, Kai (2022). DeHIN: a decentralized framework for embedding large-scale heterogeneous information networks. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-1. doi: 10.1109/TKDE.2022.3141951

Xiao, Shitao, Shao, Yingxia, Li, Yawen, Yin, Hongzhi, Shen, Yanyan and Cui, Bin (2022). LECF: recommendation via learnable edge collaborative filtering. Science China Information Sciences, 65 (1) 112101. doi: 10.1007/s11432-020-3274-6

Guo, Lei, Zhang, Jinyu, Tang, Li, Chen, Tong, Zhu, Lei and Yin, Hongzhi (2022). Time interval-enhanced graph neural network for shared-account cross-domain sequential recommendation. IEEE Transactions on Neural Networks and Learning Systems, PP (99), 1-15. doi: 10.1109/tnnls.2022.3201533

Ye, Guanhua, Yin, Hongzhi, Chen, Tong, Xu, Miao, Nguyen, Quoc Viet Hung and Song, Jiangning (2022). Personalized on-device e-health analytics with decentralized block coordinate descent. IEEE Journal of Biomedical and Health Informatics, 26 (6), 1-1. doi: 10.1109/JBHI.2022.3140455

Luo, Yadan, Huang, Zi, Chen, Hongxu, Yang, Yang, Yin, Hongzhi and Baktashmotlagh, Mahsa (2021). Interpretable signed link prediction with signed infomax hyperbolic graph. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-1. doi: 10.1109/TKDE.2021.3139035

Duong, Chi Thang, Hoang, Trung Dung, Yin, Hongzhi, Weidlich, Matthias, Nguyen, Quoc Viet Hung and Aberer, Karl (2021). Scalable robust graph embedding with Spark. Proceedings of the VLDB Endowment, 15 (4), 914-922. doi: 10.14778/3503585.3503599

Gan, Wensheng, Chen, Guoting, Yin, Hongzhi, Fournier-Viger, Philippe, Chen, Chien-Ming and Yu, Philip S. (2021). Towards Revenue Maximization with Popular and Profitable Products. ACM/IMS Transactions on Data Science, 2 (4), 1-21. doi: 10.1145/3488058

Chen, Tong, Yin, Hongzhi, Zhang, Xiangliang, Huang, Zi, Wang, Yang and Wang, Meng (2021). Quaternion factorization machines: a lightweight solution to intricate feature interaction modeling. IEEE Transactions on Neural Networks and Learning Systems, PP (99), 1-14. doi: 10.1109/TNNLS.2021.3118706

Wang, Qinyong, Yin, Hongzhi, Chen, Tong, Yu, Junliang, Zhou, Alexander and Zhang, Xiangliang (2021). Fast-adapting and privacy-preserving federated recommender system. The VLDB Journal, 31 (5), 877-896. doi: 10.1007/s00778-021-00700-6

Liu, Xueyan, Yang, Bo, Song, Wenzhuo, Musial, Katarzyna, Zuo, Wanli, Chen, Hongxu and Yin, Hongzhi (2021). A block-based generative model for attributed network embedding. World Wide Web, 24 (5), 1439-1464. doi: 10.1007/s11280-021-00918-y

Huynh, Thanh Trung, Duong, Chi Thang, Nguyen, Tam Thanh, Tong, Vinh Van, Sattar, Abdul, Yin, Hongzhi and Nguyen, Quoc Viet Hung (2021). Network alignment with holistic embeddings. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-1. doi: 10.1109/TKDE.2021.3101840

Gan, Wensheng, Lin, Jerry Chun-Wei, Zhang, Jiexiong, Yin, Hongzhi, Fournier-Viger, Philippe, Chao, Han-Chieh and Yu, Philip S. (2021). Utility mining across multi-dimensional sequences. ACM Transactions on Knowledge Discovery from Data, 15 (5) 3446938, 1-24. doi: 10.1145/3446938

Liao, Jianxin, Liu, Tongcun, Yin, Hongzhi, Chen, Tong, Wang, Jingyu and Wang, Yulong (2021). An integrated model based on deep multimodal and rank learning for point-of-interest recommendation. World Wide Web, 24 (2), 631-655. doi: 10.1007/s11280-021-00865-8

Sun, Zhenchao, Yin, Hongzhi, Chen, Hongxu, Chen, Tong, Cui, Lizhen and Yang, Fan (2021). Disease prediction via graph neural networks. IEEE Journal of Biomedical and Health Informatics, 25 (3) 9122573, 818-826. doi: 10.1109/JBHI.2020.3004143

Duong, Chi Thang, Nguyen, Tam Thanh, Yin, Hongzhi, Weidlich, Matthias, Mai, Son, Aberer, Karl and Nguyen, Quoc Viet Hung (2021). Efficient and effective multi-modal queries through heterogeneous network embedding. IEEE Transactions on Knowledge and Data Engineering, 34 (11), 1-1. doi: 10.1109/TKDE.2021.3052871

Chen, Tong, Yin, Hongzhi, Ren, Jie, Huang, Zi, Zhang, Xiangliang and Wang, Hao (2021). Uniting heterogeneity, inductiveness, and efficiency for graph representation learning. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-1. doi: 10.1109/TKDE.2021.3100529

Cui, Zhihong, Chen, Hongxu, Cui, Lizhen, Liu, Shijun, Liu, Xueyan, Xu, Guandong and Yin, Hongzhi (2021). Reinforced KGs reasoning for explainable sequential recommendation. World Wide Web, 25 (2), 631-654. doi: 10.1007/s11280-021-00902-6

Duong, Chi Thang, Hoang, Trung Dung, Yin, Hongzhi, Weidlich, Matthias, Nguyen, Quoc Viet Hung and Aberer, Karl (2021). Efficient streaming subgraph isomorphism with graph neural networks. Proceedings of the VLDB Endowment, 14 (5), 730-742. doi: 10.14778/3446095.3446097

Cui, Yi, Bai, Feifei, Yan, Ruifeng, Saha, Tapan, Mosadeghy, Mehdi, Yin, Hongzhi, Ko, Ryan K. L. and Liu, Yilu (2021). Multifractal characterization of distribution synchrophasors for cybersecurity defense of smart grids. IEEE Transactions on Smart Grid, 13 (2), 1-1. doi: 10.1109/tsg.2021.3132536

Wang, Yuandong, Yin, Hongzhi, Wu, Lian, Chen, Tong and Liu, Chunyang (2021). Secure your ride: real-time matching success rate prediction for passenger-driver pairs. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-14. doi: 10.1109/tkde.2021.3112739

Ye, Guanhua, Yin, Hongzhi, Chen, Tong, Chen, Hongxu, Cui, Lizhen and Zhang, Xiangliang (2021). FENet: A Frequency Extraction Network for Obstructive Sleep Apnea Detection. IEEE Journal of Biomedical and Health Informatics, 25 (8) 9320528, 2848-2856. doi: 10.1109/JBHI.2021.3050113

Yu, Yonghong, Jiao, Lihong, Zhou, Ningning, Zhang, Li and Yin, Hongzhi (2020). Enhanced factorization machine via neural pairwise ranking and attention networks. Pattern Recognition Letters, 140, 348-357. doi: 10.1016/j.patrec.2020.11.010

Nguyen, Tam Thanh, Huynh, Thanh Trung, Yin, Hongzhi, Tong, Vinh Van, Sakong, Darnbi, Zheng, Bolong and Nguyen, Quoc Viet Hung (2020). Entity alignment for knowledge graphs with multi-order convolutional networks. IEEE Transactions on Knowledge and Data Engineering, 34 (9), 1-1. doi: 10.1109/TKDE.2020.3038654

Yu, Junliang, Yin, Hongzhi, Li, Jundong, Gao, Min, Huang, Zi and Cui, Lizhen (2020). Enhance social recommendation with adversarial graph convolutional networks. IEEE Transactions on Knowledge and Data Engineering, 34 (8), 1-1. doi: 10.1109/tkde.2020.3033673

Ren, Xuhui, Yin, Hongzhi, Chen, Tong, Wang, Hao, Hung, Nguyen Quoc Viet, Huang, Zi and Zhang, Xiangliang (2020). CRSAL: conversational recommender systems with adversarial learning. ACM Transactions on Information Systems, 38 (4) 3394592, 1-40. doi: 10.1145/3394592

Gao, Chongming, Zhang, Zhong, Huang, Chen, Yin, Hongzhi, Yang, Qinli and Shao, Junming (2020). Semantic trajectory representation and retrieval via hierarchical embedding. Information Sciences, 538, 176-192. doi: 10.1016/j.ins.2020.05.107

Zhang, Yan, Tsang, Ivor, Yin, Hongzhi, Yang, Guowu, Lian, Defu and Li, Jingjing (2020). Deep pairwise hashing for cold-start recommendation. IEEE Transactions on Knowledge and Data Engineering, 34 (7), 1-1. doi: 10.1109/tkde.2020.3024022

Yin, Hongzhi, Wang, Qinyong, Zheng, Kai, Li, Zhixu and Zhou, Xiaofang (2020). Overcoming data sparsity in group recommendation. IEEE Transactions on Knowledge and Data Engineering, 34 (7), 1-1. doi: 10.1109/tkde.2020.3023787

Chen, Wei, Wang, Weiqing, Yin, Hongzhi, Fang, Jun-Hua and Zhao, Lei (2020). User account linkage across multiple platforms with location data. Journal of Computer Science and Technology, 35 (4), 751-768. doi: 10.1007/s11390-020-0250-7

Hosseini, Saeid, Najafipour, Saeed, Cheung, Ngai-Man, Yin, Hongzhi, Kangavari, Mohammad Reza and Zhou, Xiaofang (2020). TEAGS: time-aware text embedding approach to generate subgraphs. Data Mining and Knowledge Discovery, 34 (4), 1136-1174. doi: 10.1007/s10618-020-00688-7

Zhou, Yiming, Han, Yuehui, Liu, An, Li, Zhixu, Yin, Hongzhi, Chen, Wei and Zhao, Lei (2020). Extracting representative user subset of social networks towards user characteristics and topological features. World Wide Web, 23 (5), 2903-2931. doi: 10.1007/s11280-020-00828-5

Qiu, Ruihong, Huang, Zi, Li, Jingjing and Yin, Hongzhi (2020). Exploiting cross-session information for session-based recommendation with graph neural networks. ACM Transactions on Information Systems, 38 (3) 22, 1-23. doi: 10.1145/3382764

Chen, Hongxu, Yin, Hongzhi, Chen, Tong, Wang, Weiqing, Li, Xue and Hu, Xia (2020). Social boosted recommendation with folded bipartite network embedding. IEEE Transactions on Knowledge and Data Engineering, 34 (2), 914-926. doi: 10.1109/tkde.2020.2982878

Li, Guohui, Chen, Qi, Zheng, Bolong, Yin, Hongzhi, Nguyen, Quoc Viet Hung and Zhou, Xiaofang (2020). Group-based recurrent neural networks for POI recommendation. ACM/IMS Transactions on Data Science, 1 (1) 3, 1-18. doi: 10.1145/3343037

Huang, Jinjing, Chen, Wei, Liu, An, Wang, Weiqing, Yin, Hongzhi and Zhao, Lei (2020). Cluster query: a new query pattern on temporal knowledge graph. World Wide Web, 23 (2), 755-779. doi: 10.1007/s11280-019-00754-1

Chen, Yifan, Wang, Yang, Zhao, Xiang, Yin, Hongzhi, Markov, Ilya and De Rijke, Maarten (2020). Local variational feature-based similarity models for recommending top-N new items. ACM Transactions on Information Systems, 38 (2) 12, 1-33. doi: 10.1145/3372154

Huang, Jinjing, Chen, Wei, Li, Zhixu, Zhao, Pengpeng, Wang, Weiqing, Yin, Hongzhi and Zhao, Lei (2020). SGPM: a privacy protected approach of time-constrained graph pattern matching in cloud. World Wide Web-Internet and Web Information Systems, 23 (1), 519-547. doi: 10.1007/s11280-020-00784-0

Zhao, Yan, Zheng, Kai, Yin, Hongzhi, Liu, Guanfeng, Fang, Junhua and Zhou, Xiaofang (2020). Preference-aware task assignment in spatial crowdsourcing: from individuals to groups. IEEE Transactions on Knowledge and Data Engineering, 34 (7), 1-1. doi: 10.1109/tkde.2020.3021028

Wu, Lin, Wang, Yang, Yin, Hongzhi, Wang, Meng and Shao, Ling (2020). Few-shot deep adversarial learning for video-based person re-identification. IEEE Transactions on Image Processing, 29 8839731, 1233-1245. doi: 10.1109/tip.2019.2940684

Gao, Jiu-Ru, Chen, Wei, Xu, Jia-Jie, Liu, An, Li, Zhi-Xu, Yin, Hongzhi and Zhao, Lei (2019). An efficient framework for multiple subgraph pattern matching models. Journal of Computer Science and Technology, 34 (6), 1185-1202. doi: 10.1007/s11390-019-1969-x

Chen, Tong, Yin, Hongzhi, Chen, Hongxu, Wang, Hao, Zhou, Xiaofang and Li, Xue (2019). Online sales prediction via trend alignment-based multitask recurrent neural networks. Knowledge and Information Systems, 62 (6), 2139-2167. doi: 10.1007/s10115-019-01404-8

Sun, Xiangguo, Liu, Bo, Meng, Qing, Cao, Jiuxin, Luo, Junzhou and Yin, Hongzhi (2019). Group-level personality detection based on text generated networks. World Wide Web, 23 (3), 1887-1906. doi: 10.1007/s11280-019-00729-2

Li, Xiaocui, Yin, Hongzhi, Zhou, Ke and Zhou, Xiaofang (2019). Semi-supervised clustering with deep metric learning and graph embedding. World Wide Web, 23 (2), 781-798. doi: 10.1007/s11280-019-00723-8

Cong, Phan Thanh, Tam, Nguyen Thanh, Yin, Hongzhi, Zheng, Bolong, Stantic, Bela and Hung, Nguyen Quoc Viet (2019). Efficient user guidance for validating participatory sensing data. ACM Transactions on Intelligent Systems and Technology, 10 (4) 37, 1-30. doi: 10.1145/3326164

Khalatbari, Leila, Kangavari, M. R., Hosseini, Saeid, Yin, Hongzhi and Cheung, Ngai-Man (2019). MCP: a multi-component learning machine to predict protein secondary structure. Computers in Biology and Medicine, 110, 144-155. doi: 10.1016/j.compbiomed.2019.04.040

Hosseini, Saeid, Yin, Hongzhi, Zhou, Xiaofang, Sadiq, Shazia, Kangavari, Mohammad Reza and Cheung, Ngai-Man (2019). Leveraging multi-aspect time-related influence in location recommendation. World Wide Web, 22 (3), 1001-1028. doi: 10.1007/s11280-018-0573-2

Qian, Tieyun, Liu, Bei, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2019). Spatiotemporal representation learning for translation-based POI recommendation. ACM Transactions on Information Systems, 37 (2) 18, 1-24. doi: 10.1145/3295499

Wang, Weiqing and Yin, Hongzhi (2019). Spatiotemporal recommendation with big geo-social networking data. IET Professional Applications of Computing Series, 35, 193-224.

Du, Xingzhong, Yin, Hongzhi, Chen, Ling, Wang, Yang, Yang, Yi and Zhou, Xiaofang (2018). Personalized video recommendation using rich contents from videos. IEEE Transactions on Knowledge and Data Engineering, 32 (3) 8567986, 1-1. doi: 10.1109/TKDE.2018.2885520

Wang, Weiqing, Yin, Hongzhi, Du, Xingzhong, Nguyen, Quoc Viet Hung and Zhou, Xiaofang (2018). TPM: a temporal personalized model for spatial item recommendation. ACM Transactions on Intelligent Systems and Technology, 9 (6) a61, 1-25. doi: 10.1145/3230706

Yin, Hongzhi, Wang, Weiqing, Chen, Liang, Du, Xingzhong, Hung Nguyen, Quoc Viet and Huang, Zi (2018). Mobi-SAGE-RS: A sparse additive generative model-based mobile application recommender system. Knowledge-Based Systems, 157, 68-80. doi: 10.1016/j.knosys.2018.05.028

Zhou, Xiaofang and Yin, Hongzhi (2018). Preface. Journal of Computer Science and Technology, 33 (4), 621-624. doi: 10.1007/s11390-018-1844-1

Li, Yongjun, Peng, You, Zhang, Zhen, Wu, Mingjie, Xu, Quanqing and Yin, Hongzhi (2018). A deep dive into user display names across social networks. Information Sciences, 447, 186-204. doi: 10.1016/j.ins.2018.02.072

Li, Yongjun, Zhang, Zhen, Peng, You, Yin, Hongzhi and Xu, Quanqing (2018). Matching user accounts based on user generated content across social networks. Future Generation Computer Systems, 83, 104-115. doi: 10.1016/j.future.2018.01.041

Mansha, Sameen, Lam, Hoang Thanh, Yin, Hongzhi, Kamiran, Faisal and Ali, Mohsen (2018). Layered convolutional dictionary learning for sparse coding itemsets. World Wide Web, 22 (5), 1-15. doi: 10.1007/s11280-018-0565-2

Li, Yongjun, Peng, You, Zhang, Zhen, Yin, Hongzhi and Xu, Quanqing (2018). Matching user accounts across social networks based on username and display name. World Wide Web, 22 (3), 1-23. doi: 10.1007/s11280-018-0571-4

Wang, Yaqing, Feng, Chunyan, Chen, Ling, Yin, Hongzhi, Guo, Caili and Chu, Yunfei (2018). User identity linkage across social networks via linked heterogeneous network embedding. World Wide Web, 22 (6), 1-22. doi: 10.1007/s11280-018-0572-3

Viet Hung, Nguyen Quoc, Viet, Huynh Huu, Tam, Nguyen Thanh, Weidlich, Matthias, Yin, Hongzhi and Zhou, Xiaofang (2018). Computing crowd consensus with partial agreement. IEEE Transactions on Knowledge and Data Engineering, 30 (1), 1-14. doi: 10.1109/TKDE.2017.2750683

Yin, Hongzhi, Wang, Weiqing, Wang, Hao, Chen, Ling and Zhou, Xiaofang (2017). Spatial-aware hierarchical collaborative deep learning for POI recommendation. Ieee Transactions On Knowledge and Data Engineering, 29 (11) 8013107, 2537-2551. doi: 10.1109/TKDE.2017.2741484

Du, Xingzhong, Yin, Hongzhi, Huang, Zi, Yang, Yi and Zhou, Xiaofang (2017). Exploiting detected visual objects for frame-level video filtering. World Wide Web, 21 (5), 1-26. doi: 10.1007/s11280-017-0505-6

Hung, Nguyen Quoc Viet, Thang, Duong Chi, Tam, Nguyen Thanh, Weidlich, Matthias, Aberer, Karl, Yin, Hongzhi and Zhou, Xiaofang (2017). Answer validation for generic crowdsourcing tasks with minimal efforts. Vldb Journal, 26 (6), 855-880. doi: 10.1007/s00778-017-0484-3

Nguyen, Quoc Viet Hung, Duong, Chi Thang, Nguyen, Thanh Tam, Weidlich, Matthias, Aberer, Karl, Yin, Hongzhi and Zhou, Xiaofang (2017). Argument discovery via crowdsourcing. VLDB Journal, 26 (4), 511-535. doi: 10.1007/s00778-017-0462-9

Wang, Weiqing , Yin, Hongzhi , Chen, Ling , Sun, Yizhou , Sadiq, Shazia and Zhou, Xiaofang (2017). ST-SAGE: A Spatial-Temporal Sparse Additive Generative Model for Spatial Item Recommendation. ACM Transactions on Intelligent Systems and Technology, 8 (3) 48, 48.1-48.25. doi: 10.1145/3011019

He, Tieke, Yin, Hongzhi, Chen, Zhenyu, Zhou, Xiaofang, Sadiq, Shazia and Luo, Bin (2016). A spatial-temporal topic model for the semantic annotation of POIs in LBSNs. ACM Transactions on Intelligent Systems and Technology, 8 (1) 12, 1-24. doi: 10.1145/2905373

Yin, Hongzhi, Cui, Bin, Zhou, Xiaofang, Wang, Weiqing, Huang, Zi and Sadiq, Shazia (2016). Joint modeling of user check-in behaviors for real-time point-of-interest recommendation. ACM Transactions on Information Systems, 35 (2) 2873055, 1-44. doi: 10.1145/2873055

Shao, Y.-X., Cui, B., Ma, L. and Yin, H.-Z. (2016). A fast sketch-based approach of top-k closeness centrality search on large networks. Jisuanji Xuebao/Chinese Journal of Computers, 39 (10), 1965-1978. doi: 10.11897/SP.J.1016.2016.01965

Yin, Hongzhi, Zhou, Xiaofang, Cui, Bin, Wang, Hao, Zheng, Kai and Nguyen, Quoc Viet Hung (2016). Adapting to user interest drift for POI recommendation. IEEE Transactions on Knowledge and Data Engineering, 28 (10) 7491346, 2566-2581. doi: 10.1109/TKDE.2016.2580511

Yin, Hongzhi, Cui, Bin, Chen, Ling, Hu, Zhiting and Zhang, Chengqi (2015). Modeling location-based user rating profiles for personalized recommendation. ACM Transactions on Knowledge Discovery from Data, 9 (3) 19, 19:1-19:41. doi: 10.1145/2663356

Yin, Hongzhi, Cui, Bin, Chen, Ling, Hu, Zhiting and Zhou, Xiaofang (2015). Dynamic user modeling in social media systems. ACM Transactions on Information Systems, 33 (3) 10, 10:1-10:44. doi: 10.1145/2699670

Xie, Yiran, Yin, Hongzhi, Cui, Bin, Yao, Junjie and Xu, Quanqing (2015). Distinguishing re-sharing behaviors from re-creating behaviors in information diffusion. World Wide Web, 19 (6), 1-28. doi: 10.1007/s11280-015-0379-4

Yin, Hongzhi, Cui, Bin, Sun, Yizhou, Hu, Zhiting and Chen, Ling (2014). LCARS: A spatial item recommender system. ACM Transactions on Information Systems, 32 (3) 11, 11-11. doi: 10.1145/2629461

Conference Papers

Xia, Xin, Yu, Junliang, Xu, Guandong and Yin, Hongzhi (2023). Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation. New York, NY, USA: ACM. doi: 10.1145/3583780.3615088

Liu, Yi, Xuan, Hongrui, Li, Bohan, Wang, Meng, Chen, Tong and Yin, Hongzhi (2023). Self-Supervised Dynamic Hypergraph Recommendation based on Hyper-Relational Knowledge Graph. New York, NY, USA: ACM. doi: 10.1145/3583780.3615054

Wang, Zongwei, Gao, Min, Li, Wentao, Yu, Junliang, Guo, Linxin and Yin, Hongzhi (2023). Efficient Bi-Level Optimization for Recommendation Denoising. New York, NY, USA: ACM. doi: 10.1145/3580305.3599324

Qu, Yunke, Chen, Tong, Zhao, Xiangyu, Cui, Lizhen, Zheng, Kai and Yin, Hongzhi (2023). Continuous input embedding size search for recommender systems. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23-27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591653

Zheng, Shangfei, Yin, Hongzhi, Chen, Tong, Nguyen, Quoc Viet Hung, Chen, Wei and Zhao, Lei (2023). DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning. New York, NY, USA: ACM. doi: 10.1145/3539618.3591671

Long, Jing, Chen, Tong, Nguyen, Quoc Viet Hung, Xu, Guandong, Zheng, Kai and Yin, Hongzhi (2023). Model-agnostic decentralized collaborative learning for on-device POI recommendation. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23-27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591733

Yuan, Wei, Nguyen, Quoc Viet Hung, He, Tieke, Chen, Liang and Yin, Hongzhi (2023). Manipulating federated recommender systems: poisoning with synthetic users and its countermeasures. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23-27 July 2023. New York, NY, United States: ACM. doi: 10.1145/3539618.3591722

Yuan, Wei, Yang, Chaoqun, Nguyen, Quoc Viet Hung, Cui, Lizhen, He, Tieke and Yin, Hongzhi (2023). Interaction-level membership inference attack against federated recommender systems. The ACM Web Conference 2023, Austin, TX, United States, 30 April - 4 May 2023. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3543507.3583359

Qu, Liang, Tang, Ningzhi, Zheng, Ruiqi, Nguyen, Quoc Viet Hung, Huang, Zi, Shi, Yuhui and Yin, Hongzhi (2023). Semi-decentralized federated ego graph learning for recommendation. The ACM Web Conference 2023, Austin, TX, United States, 30 April - 4 May 2023. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3543507.3583337

Tam Nguyen, Thanh, Thang Duong, Chi, Yin, Hongzhi, Weidlich, Matthias, Son Mai, Thai, Aberer, Karl and Viet Hung Nguyen, Quoc (2023). Efficient and Effective Multi-Modal Queries through Heterogeneous Network Embedding (Extended Abstract). IEEE. doi: 10.1109/icde55515.2023.00322

Zhang, Yufeng, Wang, Weiqing, Yin, Hongzhi, Zhao, Pengpeng, Chen, Wei and Zhao, Lei (2023). Disconnected emerging knowledge graph oriented inductive link prediction. 2023 IEEE 39th International Conference on Data Engineering (ICDE), Anaheim, CA, United States, 3-7 April 2023. Piscataway, NJ, United States: IEEE. doi: 10.1109/icde55515.2023.00036

Zheng, Shangfei, Wang, Weiqing, Qu, Jianfeng, Yin, Hongzhi, Chen, Wei and Zhao, Lei (2023). MMKGR: Multi-hop multi-modal knowledge graph reasoning. 2023 IEEE 39th International Conference on Data Engineering (ICDE), Anaheim, CA, United States, 3-7 April 2023. Piscataway, NJ, United States: IEEE. doi: 10.1109/icde55515.2023.00015

He, Li, Wang, Xianzhi, Wang, Dingxian, Zou, Haoyuan, Yin, Hongzhi and Xu, Guandong (2023). Simplifying graph-based collaborative filtering for recommendation. Sixteenth ACM International Conference on Web Search and Data Mining, Singapore, Singapore, 27 February - 3 March 2023. New York, NY, United States: ACM. doi: 10.1145/3539597.3570451

Yuan, Wei, Yin, Hongzhi, Wu, Fangzhao, Zhang, Shijie, He, Tieke and Wang, Hao (2023). Federated unlearning for on-device recommendation. Sixteenth ACM International Conference on Web Search and Data Mining, Singapore, Singapore, 27 February - 3 March 2023. New York, NY, United States: ACM. doi: 10.1145/3539597.3570463

Yang, Cheng, Guo, Yuxin, Xu, Yao, Shi, Chuan, Liu, Jiawei, Wang, Chunchen, Li, Xin, Guo, Ning and Yin, Hongzhi (2023). Learning to distill graph neural networks. Sixteenth ACM International Conference on Web Search and Data Mining, Singapore, Singapore, 27 February - 3 March 2023. New York, NY, United States: ACM. doi: 10.1145/3539597.3570480

Xuan, Hongrui, Liu, Yi, Li, Bohan and Yin, Hongzhi (2023). Knowledge enhancement for contrastive multi-behavior recommendation. Sixteenth ACM International Conference on Web Search and Data Mining, Singapore, Singapore, 27 February - 3 March 2023. New York, NY, United States: ACM. doi: 10.1145/3539597.3570386

Qiu, Ruihong, Huang, Zi and Yin, Hongzhi (2023). Beyond double ascent via recurrent neural tangent kernel in sequential recommendation. 22nd IEEE International Conference on Data Mining (ICDM), Orlando, FL USA, 28 November-1 December 2022. New York, NY USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/icdm54844.2022.00053

Liu, Jie, He, Mengting, Wang, Guangtao, Nguyen, Quoc Viet Hung, Shang, Xuequn and Yin, Hongzhi (2023). Imbalanced node classification beyond homophilic assumption. Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23), Macao, SAR, 19-25 August 2023. Palo Alto, CA, United States: AAAI Press. doi: 10.24963/ijcai.2023/848

Mansha, Sameen, Rehman, Abdur, Abdullah, Shaaf, Kamiran, Faisal and Yin, Hongzhi (2022). Locality aware temporal FMs for crime prediction. 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, United States, 17-21 October 2022. New York, NY, United States: ACM. doi: 10.1145/3511808.3557657

Yuan, Wei, Zhang, Quanjun, He, Tieke, Fang, Chunrong, Hung, Nguyen Quoc Viet, Hao, Xiaodong and Yin, Hongzhi (2022). CIRCLE: continual repair across programming languages. ISSTA '22: 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, Online, 18 - 22 July 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3533767.3534219

Chen, Tong, Yin, Hongzhi, Long, Jing, Nguyen, Quoc Viet Hung, Wang, Yang and Wang, Meng (2022). Thinking inside The Box : Learning Hypercube Representations for Group Recommendation. SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11 - 15 July 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3477495.3532066

Qu, Liang, Ye, Yonghong, Tang, Ningzhi, Zhang, Lixin, Shi, Yuhui and Yin, Hongzhi (2022). Single-shot Embedding Dimension Search in Recommender System. SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11 - 15 July 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3477495.3532060

Xia, Xin, Yin, Hongzhi, Yu, Junliang, Wang, Qinyong, Xu, Guandong and Nguyen, Quoc Viet Hung (2022). On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation. SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11 - 15 July 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3477495.3531775

Yu, Junliang, Yin, Hongzhi, Xia, Xin, Chen, Tong, Cui, Lizhen and Nguyen, Quoc Viet Hung (2022). Are Graph Augmentations Necessary? : Simple Graph Contrastive Learning for Recommendation. SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11 - 15 July 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3477495.3531937

Chen, Tong, Yin, Hongzhi, Ren, Jie, Huang, Zi, Zhang, Xiangliang and Wang, Hao (2022). Uniting heterogeneity, inductiveness, and efficiency for graph representation learning (Extended Abstract). 2022 IEEE 38th International Conference on Data Engineering (ICDE), Kuala Lumpur, Malaysia, 9-12 May 2022. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/icde53745.2022.00143

Phan, Thanh Cong, Nguyen, Thanh Tam, Weidlich, Matthias, Yin, Hongzhi, Jo, Jun and Nguyen, Quoc Viet Hung (2022). exRumourLens: Auditable Rumour Detection with Multi-View Explanations. 2022 IEEE 38th International Conference on Data Engineering (ICDE), Kuala Lumpur, Malaysia, 9-12 May 2022. Piscataway, NJ United States: IEEE. doi: 10.1109/icde53745.2022.00291

Zhang, Yan, Li, Changyu, Tsang, Ivor W., Xu, Hui, Duan, Lixin, Yin, Hongzhi, Li, Wen and Shao, Jie (2022). Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations. 2022 IEEE 38th International Conference on Data Engineering (ICDE), Kuala Lumpur, Malaysia, 9-12 May 2022. Piscataway, NJ United States: IEEE. doi: 10.1109/icde53745.2022.00265

Huynh, Thanh Trung, Duong, Thang Chi, Nguyen, Thanh Tam, Tong, Van Vinh, Sattar, Abdul, Yin, Hongzhi and Nguyen, Quoc Viet Hung (2022). Network Alignment with Holistic Embeddings (Extended Abstract). 2022 IEEE 38th International Conference on Data Engineering (ICDE), Kuala Lumpur, Malaysia, 9-12 May 2022. Piscataway, NJ United States: IEEE. doi: 10.1109/icde53745.2022.00131

Yuan, Wei, Yin, Hongzhi, He, Tieke, Chen, Tong, Wang, Qiufeng and Cui, Lizhen (2022). Unified question generation with continual lifelong learning. WWW 2022 - ACM Web Conference 2022, Virtual Event, Lyon, France, 25-29 April 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3485447.3511930

Wang, Yanling, Zhang, Jing, Li, Haoyang, Dong, Yuxiao, Yin, Hongzhi, Li, Cuiping and Chen, Hong (2022). ClusterSCL: Cluster-Aware Supervised Contrastive Learning on Graphs. WWW '22: The ACM Web Conference 2022, Lyon, France, 25 - 29 April 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3485447.3512207

Tommasini, Riccardo, Roy, Senjuti Basu, Wang, Xuan, Wang, Hongwei, Ji, Heng, Han, Jiawei, Nakov, Preslav, Da San Martino, Giovanni, Alam, Firoj, Schedl, Markus, Lex, Elisabeth, Bharadwaj, Akash, Cormode, Graham, Dojchinovski, Milan, Forberg, Jan, Frey, Johannes, Bonte, Pieter, Balduini, Marco, Belcao, Matteo, Della Valle, Emanuele, Yu, Junliang, Yin, Hongzhi, Chen, Tong, Liu, Haochen, Wang, Yiqi, Fan, Wenqi, Liu, Xiaorui, Dacon, Jamell, Lye, Lingjuan ... He, Xiangnan (2022). Accepted Tutorials at The Web Conference 2022. The Web Conference 2022, Lyon, France, 25 – 29 April 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3487553.3547182

Zhang, Shijie, Yin, Hongzhi, Chen, Tong, Huang, Zi, Nguyen, Quoc Viet Hung and Cui, Lizhen (2022). PipA!ack: poisoning federated recommender systems for manipulating item promotion. WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, Virtual, AZ, United States, 21 - 25 February 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3488560.3498386

Qiu, Ruihong, Huang, Zi, Yin, Hongzhi and Wang, Zijian (2022). Contrastive learning for representation degeneration problem in sequential recommendation. WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, Virtual, AZ, United States, 21 - 25 February 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3488560.3498433

Zhao, Weibin, Zhang, Aoran, Shang, Lin, Yu, Yonghong, Zhang, Li, Wang, Can, Chen, Jiajun and Yin, Hongzhi (2022). Hyperbolic personalized tag recommendation. 27th International Conference on Database Systems for Advanced Applications (DASFAA-2022), Virtual , 11-14 April 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-00126-0_14

Qian, Biao, Wang, Yang, Yin, Hongzhi, Hong, Richang and Wang, Meng (2022). Switchable online knowledge distillation. 17th European Conference on Computer Vision, ECCV 2022, Tel Aviv, Israel, October 23-27, 2022. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-031-20083-0_27

Liu, Yi, Li, Bohan, Zang, Yalei, Li, Aoran and Yin, Hongzhi (2021). A knowledge-aware recommender with attention-enhanced dynamic convolutional network. CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual, 1-5 November 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3459637.3482406

Mansha, Sameen, Khalid, Tayyab, Kamiran, Faisal, Hussain, Masroor, Hussain, Syed Fawad and Yin, Hongzhi (2021). GDFM: Gene Vectors Embodied Deep Attentional Factorization Machines for Interaction prediction. CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual, 1-5 November 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3459637.3482110

Li, Yang, Chen, Tong, Zhang, Peng-Fei and Yin, Hongzhi (2021). Lightweight self-attentive sequential recommendation. CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual, 1-5 November 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3459637.3482448

Zhang, Xuyun, Puthal, Deepak Kumar, Yang, Chi, Choo, Kim-Kwang Raymond, Yin, Hongzhi and Liu, Guanfeng (2021). International Workshop on Privacy, Security and Trust in Computational Intelligence (PSTCI2021). CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual, 1-5 November 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3459637.3482043

Cui, Lizhen, Shao, Yingxia, Yu, Junliang, Yin, Hongzhi and Xia, Xin (2021). Self-supervised graph co-training for session-based recommendation. CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual, 1-5 November 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3459637.3482388

Zhang, Junwei, Gao, Min, Yu, Junliang, Guo, Lei, Li, Jundong and Yin, Hongzhi (2021). Double-scale self-supervised hypergraph learning for group recommendation. CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual, 1-5 November 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3459637.3482426

Zhang, Peng-Fei, Duan, Jiasheng, Huang, Zi and Yin, Hongzhi (2021). Joint-teaching: learning to refine knowledge for resource-constrained unsupervised cross-modal retrieval. MM '21: ACM Multimedia Conference, Virtual, 20-24 October 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3474085.3475286

Qiu, Ruihong, Wang, Sen, Chen, Zhi, Yin, Hongzhi and Huang, Zi (2021). CausalRec: causal inference for visual debiasing in visually-aware recommendation. MM '21: ACM Multimedia Conference, Virtual, 20-24 October 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3474085.3475266

Qu, Liang, Zhu, Huaisheng, Zheng, Ruiqi, Shi, Yuhui and Yin, Hongzhi (2021). ImGAGN: imbalanced network embedding via generative adversarial graph networks. 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Virtual (Singapore), 14-18 August 2021. New York, NY, United States: ACM. doi: 10.1145/3447548.3467334

Chen, Tong, Yin, Hongzhi, Zheng, Yujia, Huang, Zi, Wang, Yang and Wang, Meng (2021). Learning elastic embeddings for customizing on-device recommenders. 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Virtual (Singapore), 14-18 August 2021. New York, NY, United States: ACM. doi: 10.1145/3447548.3467220

Yu, Junliang, Yin, Hongzhi, Gao, Min, Xia, Xin, Zhang, Xiangliang and Viet Hung, Nguyen Quoc (2021). Socially-aware self-supervised tri-training for recommendation. 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Virtual (Singapore), 14-18 August 2021. New York, NY, United States: ACM. doi: 10.1145/3447548.3467340

Sun, Xiangguo, Yin, Hongzhi, Liu, Bo, Chen, Hongxu, Cao, Jiuxin, Shao, Yingxia and Viet Hung, Nguyen Quoc (2021). Heterogeneous hypergraph embedding for graph classification. WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, Virtual Event, 8-12 March 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3437963.3441835

Hao, Bowen, Zhang, Jing, Yin, Hongzhi, Li, Cuiping and Chen, Hong (2021). Pre-training graph neural networks for cold-start users and items representation. WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, Virtual Event, 8-12 March 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3437963.3441738

Chen, Hongxu, Li, Yicong, Sun, Xiangguo, Xu, Guandong and Yin, Hongzhi (2021). Temporal meta-path guided explainable recommendation. WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, Virtual Event Israel, 8 - 12 March 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3437963.3441762

Li, Yang, Chen, Tong, Luo, Yadan, Yin, Hongzhi and Huang, Zi (2021). Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, QC Canada, 19 - 27 August 2021. Palo Alto, CA United States: A A A I Press. doi: 10.24963/ijcai.2021/206

Zhang, Sixiao, Chen, Hongxu, Ming, Xiao, Cui, Lizhen, Yin, Hongzhi and Xu, Guandong (2021). Where are we in embedding spaces?. KDD '21: 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Singapore, Singapore, 14 - 18 August 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3447548.3467421

Guo, Lei, Tang, Li, Chen, Tong, Zhu, Lei, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2021). DA-GCN: a domain-aware attentive graph convolution network for shared-account cross-domain sequential recommendation. International Joint Conference on Artificial Intelligence, Montreal, Canada, 19-27 August 2021. San Francisco, CA, United States: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2021/342

Ren, Xuhui, Yin, Hongzhi, Chen, Tong, Wang, Hao, Huang, Zi and Zheng, Kai (2021). Learning to ask appropriate questions in conversational recommendation. SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, 11-15 July 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3404835.3462839

Liang, Yile, Qian, Tieyun, Li, Qing and Yin, Hongzhi (2021). Enhancing domain-level and user-level adaptivity in diversified recommendation. SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, 11-15 July 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3404835.3462957

Zhang, Peng-Fei, Li, Yang, Huang, Zi and Yin, Hongzhi (2021). Privacy protection in deep multi-modal retrieval. 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual, 11-15 July 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3404835.3462837

Wang, Yanling, Zhang, Jing, Guo, Shasha, Yin, Hongzhi, Li, Cuiping and Chen, Hong (2021). Decoupling representation learning and classification for GNN-based anomaly detection. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual, 11-15 July 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3404835.3462944

Xia, Xin, Yin, Hongzhi, Yu, Junliang, Wang, Qinyong, Cui, Lizhen and Zhang, Xiangliang (2021). Self-supervised hypergraph convolutional networks for session-based recommendation. Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Virtual, 2-9 February 2021. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence.

Yu, Junliang, Yin, Hongzhi, Li, Jundong, Wang, Qinyong, Hung, Nguyen Quoc Viet and Zhang, Xiangliang (2021). Self-supervised multi-channel hypergraph convolutional network for social recommendation. WWW '21: Proceedings of the Web Conference 2021, Ljubljana, Slovenia, 19-23 April 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3442381.3449844

Zhang, Chen, Wang, Hao, Jiang, Feijun and Yin, Hongzhi (2021). Adapting to context-aware knowledge in natural conversation for multi-turn response selection. WWW '21: Proceedings of the Web Conference 2021, Ljubljana, Slovenia, 19-23 April 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3442381.3449902

Sun, Xiangguo, Yin, Hongzhi, Liu, Bo, Chen, Hongxu, Meng, Qing, Han, Wang and Cao, Jiuxin (2021). Multi-level hyperedge distillation for social linking prediction on sparsely observed networks. WWW '21: Proceedings of the Web Conference 2021, Ljubljana, Slovenia, 19-23 April 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3442381.3449912

Zhang, Shijie, Yin, Hongzhi, Chen, Tong, Huang, Zi, Cui, Lizhen and Zhang, Xiangliang (2021). Graph embedding for recommendation against attribute inference attacks. WWW '21: Proceedings of the Web Conference 2021, Ljubljana, Slovenia, 19-22 April 2021. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3442381.3449813

Tam, Nguyen Thanh, Trung, Huynh Thanh, Yin, Hongzhi, Van Vinh, Tong, Sakong, Darnbi, Zheng, Bolong and Hung, Nguyen Quoc Viet (2021). Entity alignment for knowledge graphs with multi-order convolutional networks (extended abstract). 2021 IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, 19-22 April 2021. Washington, DC USA: IEEE Computer Society. doi: 10.1109/ICDE51399.2021.00247

Imran, Mubashir, Yin, Hongzhi, Chen, Tong, Huang, Zi, Zhang, Xiangliang and Zheng, Kai (2021). DDHH: A decentralized deep learning framework for large-scale heterogeneous networks. 2021 IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, 19-22 April 2021. Washington, DC USA: IEEE Computer Society. doi: 10.1109/ICDE51399.2021.00196

Wang, Yuandong, Yin, Hongzhi, Chen, Tong, Liu, Chunyang, Wang, Ben, Wo, Tianyu and Xu, Jie (2021). Gallat: A spatiotemporal graph attention network for passenger demand prediction. 2021 IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, 19-22 April 2021. Washington, DC USA: IEEE Computer Society. doi: 10.1109/ICDE51399.2021.00212

Lyu, Yanzhang, Yin, Hongzhi, Liu, Jun, Liu, Mengyue, Liu, Huan and Deng, Shizhuo (2021). Reliable recommendation with review-level explanations. 2021 IEEE 37th International Conference on Data Engineering (ICDE), Chania, Greece, 19-22 April 2021. Washington, DC USA: IEEE Computer Society. doi: 10.1109/ICDE51399.2021.00137

Hao, Bowen, Zhang, Jing, Li, Cuiping, Chen, Hong and Yin, Hongzhi (2021). Recommending courses in MOOCs for jobs: an auto weak supervision approach. European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, Virtual, 14-18 September 2021. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-030-67667-4_3

Zhao, Yan, Zhou, Lianming, Deng, Liwei, Zheng, Vincent W., Yin, Hongzhi and Zheng, Kai (2021). Subgraph convolutional network for recommendation. 2021 IEEE 7th International Conference on Cloud Computing and Intelligent Systems (CCIS), Xi'an, China, 7-8 November 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers . doi: 10.1109/CCIS53392.2021.9754683

Qiu, Ruihong, Huang, Zi and Yin, Hongzhi (2021). Memory augmented multi-instance contrastive predictive coding for sequential recommendation. IEEE International Conference on Data Mining, Auckland, New Zealand, 7-10 December 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM51629.2021.00063

Xia, Xin, Yin, Hongzhi, Yu, Junliang, Wang, Qinyong, Cui, Lizhen and Zhang, Xiangliang (2021). Self-supervised hypergraph convolutional networks for session-based recommendation. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence, Virtual, 2-9 February 2021. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence Press.

Chen, Hongxu, Yin, Hongzhi, Sun, Xiangguo, Chen, Tong, Gabrys, Bogdan and Musial, Katarzyna (2020). Multi-level graph convolutional networks for cross-platform Anchor Link Prediction. ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Virtual Event, CA, United States, 23-27 August 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3394486.3403201

Chen, Tong, Yin, Hongzhi, Ye, Guanhua, Huang, Zi, Wang, Yang and Wang, Meng (2020). Try this instead: personalized and interpretable substitute recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China, 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401042

Qiu, Ruihong, Yin, Hongzhi, Huang, Zi and Chen, Tong (2020). GAG: global attributed graph neural network for streaming session-based recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China , 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401109

Nguyen, Thanh Tam, Weidlich, Matthias, Yin, Hongzhi, Zheng, Bolong, Nguyen, Quang Huy and Nguyen, Quoc Viet Hung (2020). FactCatch: incremental pay-as-you-go fact checking with minimal user effort. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China, 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401408

Zhao, Kangzhi, Zhang, Yong, Yin, Hongzhi, Wang, Jin, Zheng, Kai, Zhou, Xiaofang and Xing, Chunxiao (2020). Discovering subsequence patterns for next POI recommendation. Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20), Yokohama, Japan, 11-17 July, 2020. California, United States: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2020/445

Duong, Chi Thang, Yin, Hongzhi, Hoang, Dung, Nguyen, Minn Hung, Weidlich, Matthias, Hung Nguyen, Quoc Viet and Aberer, Karl (2020). Graph embeddings for one-pass processing of heterogeneous queries. 2020 IEEE 36th International Conference on Data Engineering (ICDE), Dallas, TX, United States, 20-24 April 2020. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/ICDE48307.2020.00222

Imran, Mubashir, Yin, Hongzhi, Chen, Tong, Shao, Yingxia, Zhang, Xiangliang and Zhou, Xiaofang (2020). Decentralized embedding framework for large-scale networks. International Conference on Database Systems for Advanced Applications, Jeju, South Korea, 24-27 September 2020. Heidelberg, Germany: Springer . doi: 10.1007/978-3-030-59419-0_26

Jiao, Lihong, Yu, Yonghong, Zhou, Ningning, Zhang, Li and Yin, Hongzhi (2020). Neural pairwise ranking factorization machine for item recommendation. International Conference on Database Systems for Advanced Applications, Jeju, South Korea, 24-27 September 2020. Heidelberg, Germany: Springer . doi: 10.1007/978-3-030-59410-7_46

Guo, Lei, Yin, Hongzhi, Wang, Qinyong, Cui, Bin, Huang, Zi and Cui, Lizhen (2020). Group recommendation with latent voting mechanism. 2020 IEEE 36th International Conference on Data Engineering (ICDE), Dallas, TX, United States, 20-24 April 2020. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/ICDE48307.2020.00018

Yang, Yu, Wen, Zhiyuan, Cao, Jiannong, Shen, Jiaxing, Yin, Hongzhi and Zhou, Xiaofang (2020). EPARS: Early prediction of at-risk students with online and offline learning behaviors. International Conference on Database Systems for Advanced Applications, Jeju, South Korea, 24-27 September 2020. Heidelberg, Germany: Springer . doi: 10.1007/978-3-030-59416-9_1

Zhang, Shijie, Yin, Hongzhi, Chen, Tong, Hung, Quoc Viet Nguyen, Huang, Zi and Cui, Lizhen (2020). GCN-based user representation learning for unifying robust recommendation and fraudster detection. SIGIR '20: 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Online, July 2020. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3397271.3401165

Wang, Qinyong, Yin, Hongzhi, Chen, Tong, Huang, Zi, Wang, Hao, Zhao, Yanchang and Viet Hung, Nguyen Quoc (2020). Next point-of-interest recommendation on resource-constrained mobile devices. WWW '20: The Web Conference 2020, Taipei, Taiwan, April 2020. New York, United States: Association for Computing Machinery. doi: 10.1145/3366423.3380170

Trung, Huynh Thanh, Van Vinh, Tong, Tam, Nguyen Thanh, Yin, Hongzhi, Weidlich, Matthias and Viet Hung, Nguyen Quoc (2020). Adaptive network alignment with unsupervised and multi-order convolutional networks. 2020 IEEE 36th International Conference on Data Engineering (ICDE), Dallas, TX, United States, 20-24 April 2020. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/ICDE48307.2020.00015

Sun, Ke, Qian, Tieyun, Chen, Tong, Liang, Yile, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2020). Where to go next: modeling long- and short-term user preferences for point-of-interest recommendation. AAAI Conference on Artificial Intelligence, New York, NY, United States, 7-12 February 2020. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v34i01.5353

Chen, Tong, Yin, Hongzhi, Nguyen, Quoc Viet Hung, Peng, Wen-Chih, Li, Xue and Zhou, Xiaofang (2020). Sequence-aware factorization machines for temporal predictive analytics. 2020 IEEE 36th International Conference on Data Engineering, Dallas, Texas, United States, 20-24 April 2020. LOS ALAMITOS: IEEE Computer Society. doi: 10.1109/ICDE48307.2020.00125

Shang, Mingyue, Fu, Zhenxin, Yin, Hongzhi, Tang, Bo, Zhao, Dongyan and Yan, Rui (2019). Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?. The Thirty-Third AAAI Conference on Artificial Intelligence, Honolulu, HI United States, 27 January – 1 February 2019. Menlo Park, CA United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v33i01.330110031

Wang, Qinyong, Nguyen, Quoc Viet Hung, Yin, Hongzhi, Huang, Zi, Wang, Hao and Cui, Lizhen (2019). Enhancing collaborative filtering with generative augmentation. 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), Anchorage, AK United States, 4-8 August 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3292500.3330873

Zhang, Rui, Li, Jianxin, Yin, Hongzhi, Reynolds, Mark, Cheema, Muhammad Aamir and Chen, Ling (2019). IWSC 2017 chairs' welcome. International Conference on World Wide Web , Perth, WA, Australia, 3-7 April 2017. Geneva, Switzerland: International World Wide Web Conferences Steering Committee.

Wang, Yuandong, Wo, Tianyu, Yin, Hongzhi, Xu, Jie, Chen, Hongxu and Zheng, Kai (2019). Origin-destination matrix prediction via graph convolution: A new perspective of passenger demand modeling. 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), Anchorage, AK United States, 4-8 August 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3292500.3330877

Sun, Ke, Qian, Tieyun, Yin, Hongzhi, Chen, Tong, Chen, Yiqi and Chen, Ling (2019). What can history tell us? Identifying relevant sessions for next-item recommendation. 28th ACM International Conference on Information and Knowledge Management, Beijing, China, 3-7 November 2019. New York, United States: Association for Computing Machinery. doi: 10.1145/3357384.3358050

Yu, Junliang, Gao, Min, Yin, Hongzhi, Li, Jundong, Gao, Chongming and Wang, Qinyong (2019). Generating reliable friends via adversarial training to improve social recommendation. IEEE International Conference on Data Mining , Beijing, China, 8-11 November 2019. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDM.2019.00087

Guo, Lei, Chen, Tong, Yin, Hongzhi, Zhou, Alexander, Wang, Qinyong and Hung, Nguyen Quoc Viet (2019). Streaming Session-based Recommendation. 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), Anchorage, AK United States, 4-8 August 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3292500.3330839

Chen, Tong, Yin, Hongzhi, Chen, Hongxu, Yan, Rui, Nguyen, Quoc Viet Hung and Li, Xue (2019). AIR: Attentional intention-aware recommender systems. IEEE 35th International Conference on Data Engineering (ICDE), Macau, China, 8-11 April 2019. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/ICDE.2019.00035

Zhang, Shijie, Yin, Hongzhi, Wang, Qinyong, Chen, Tong, Chen, Hongxu and Nguyen, Quoc Viet Hung (2019). Inferring substitutable products with deep network embedding. International Joint Conference on Artificial Intelligence, Macao, China, 10-16 August 2019. California: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2019/598

Wang, Qinyong, Yin, Hongzhi, Wang, Weiqing, Huang, Zi, Guo, Guibing and Nguyen, Quoc Viet Hung (2019). Multi-hop path queries over knowledge graphs with neural memory networks. 24th International Conference on Database Systems for Advanced Applications, DASFAA 2019, Chiang Mai, Thailand, 22 - 25 April 2019. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-18576-3_46

Qiu, Ruihong, Li, Jingjing, Huang, Zi and Yin, Hongzhi (2019). Rethinking the item order in session-based recommendation with graph neural networks. CIKM '19 28th ACM International Conference on Information and Knowledge Management, Beijing, China, 3 - 7 November, 2019. New York, New York, USA: ACM Press. doi: 10.1145/3357384.3358010

Wang, Weiqing, Yin, Hongzhi, Du, Xingzhong, Hua, Wen, Li, Yongjun and Nguyen, Quoc Viet Hung (2019). Online user representation learning across heterogeneous social networks. 42nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), Paris, France, 21-25 July 2019. New York, NY, United States: Association for Computing Machinery (ACM). doi: 10.1145/3331184.3331258

Shang, Mingyue, Fu, Zhenxin, Yin, Hongzhi, Tang, Bo, Zhao, Dongyan and Yan, Rui (2019). Find a reasonable ending for stories: Does logic relation help the story cloze test?. 33rd AAAI Conference on Artificial Intelligence / 31st Innovative Applications of Artificial Intelligence Conference / 9th AAAI Symposium on Educational Advances in Artificial Intelligence, Honolulu, HI, United States, 27 January - 1 February, 2019. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence.

Li, Xiaocui, Yin, Hongzhi, Zhou, Ke, Chen, Hongxu, Sadiq, Shazia and Zhou, Xiaofang (2019). Semi-supervised Clustering with Deep Metric Learning. 24th International Conference on Database Systems for Advanced Applications, DASFAA 2019, Chiang Mai, Thailand, 22-15 April 2019. Heidelberg, Germany: Springer . doi: 10.1007/978-3-030-18590-9_50

Gao, Chongming, Yuan, Shuai, Zhang, Zhong, Yin, Hongzhi and Shao, Junming (2019). BLOMA: explain collaborative filtering via Boosted Local rank-One Matrix Approximation. 24th International Conference on Database Systems for Advanced Applications, DASFAA 2019, Chiang Mai, Thailand, 22-25 April 2019. Philadelphia, PA, United States: Elsevier. doi: 10.1007/978-3-030-18590-9_72

Chen, Hongxu, Yin, Hongzhi, Chen, Tong, Nguyen, Quoc Viet Hung, Peng, Wen-Chih and Li, Xue (2019). Exploiting centrality information with graph convolutions for network representation learning. IEEE 35th International Conference on Data Engineering (ICDE), Macau, China, 8-11 April 2019. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/ICDE.2019.00059

Yin, Hongzhi, Wang, Qinyong, Zheng, Kai, Li, Zhixu, Yang, Jiali and Zhou, Xiaofang (2019). Social influence-based group representation learning for group recommendation. 35th International Conference on Data Engineering (ICDE 2019), Macao, Macao, 8-11 April 2019. New York, NY, United States: IEEE Computer Society. doi: 10.1109/ICDE.2019.00057

Wang, Ziwei, Luo, Yadan, Li, Yang, Huang, Zi and Yin, Hongzhi (2018). Look deeper see richer: Depth-aware image paragraph captioning. 26th ACM Multimedia conference, MM 2018, Seoul, South Korea, October 22 - 26, 2018. New York, NY, Untied States: Association for Computing Machinery, Inc. doi: 10.1145/3240508.3240583

Nguyen, Quoc Viet Hung, Zheng, Kai, Weidlich, Matthias, Zheng, Bolong, Yin, Hongzhi, Nguyen, Thanh Tam and Stantic, Bela (2018). What-If analysis with conflicting goals: recommending data ranges for exploration. 34th IEEE International Conference on Data Engineering, ICDE 2018, Paris, France, April 16 - 19, 2018. Los Alamitos, CA, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDE.2018.00018

Gao, Jiuru, Xu, Jiajie, Liu, Guanfeng, Chen, Wei, Yin, Hongzhi and Zhao, Lei (2018). A privacy-preserving framework for subgraph pattern matching in cloud. 23rd International Conference on Database Systems for Advanced Applications DASFAA 2018, Gold Coast, QLD Australia, 21 - 24 May 2018. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-91452-7_20

Hosseini, Saeid, Yin, Hongzhi, Zhang, Meihui, Elovici, Yuval and Zhou, Xiaofang (2018). Mining subgraphs from propagation networks through temporal dynamic analysis. 19th IEEE International Conference on Mobile Data Management, MDM 2018, Aalborg University, Aalborg, Denmark, 26-28 June 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/MDM.2018.00023

Nguyen, Thanh Tam, Weidlich, Matthias, Yin, Hongzhi, Zheng, Bolong, Hung Nguyen, Quoc Viet and Stantic, Bela (2018). User guidance for efficient fact checking. 45th International Conference on Very Large Data Bases, Los Angeles, CA United States, 2019. New York, NY United States: Association for Computing Machinery. doi: 10.14778/3324301.3324303

Hosseini, Saeid, Yin, Hongzhi, Cheung, Ngai-Man, Leng, Kan Pak, Elovici, Yuval and Zhou, Xiaofang (2018). Exploiting reshaping subgraphs from bilateral propagation graphs. 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, Gold Coast, QLD, Australia, 21-24 May 2018. Cham, Switzerland: Springer Verlag. doi: 10.1007/978-3-319-91452-7_23

Chen, Tong, Yin, Hongzhi, Chen, Hongxu, Wu, Lin, Wang, Hao, Zhou, Xiaofang and Li, Xue (2018). TADA: trend alignment with dual-attention multi-task recurrent neural networks for sales prediction. 18th IEEE International Conference on Data Mining, ICDM 2018, Singapore, 17-20 November 2018. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/ICDM.2018.00020

Yin, Hongzhi, Zou, Lei, Nguyen, Quoc Viet Hung, Huang, Zi and Zhou, Xiaofang (2018). Joint event-partner recommendation in event-based social networks. 34th IEEE International Conference on Data Engineering (ICDE 2018), Paris, France, 16-19 April 2018. NEW YORK: IEEE. doi: 10.1109/ICDE.2018.00088

Yin, Hongzhi and Wang, Weiqing (2018). Mining geo-social networks - spatial item recommendation. 29th Australasian Database Conference (ADC), Gold Coast, Australia, 24-27 May 2018. Cham, Switzerland: Springer.

Yu, Junliang, Gao, Min, Li, Jundong, Yin, Hongzhi and Liu, Huan (2018). Adaptive implicit friends identification over heterogeneous network for social recommendation. 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, 22-26 October 2018. New York, NY, United States: Association for Computing Machinery (ACM). doi: 10.1145/3269206.3271725

Chen, Wei, Yin, Hongzhi, Wang, Weiqing, Zhao, Lei and Zhou, Xiaofang (2018). Effective and efficient user account linkage across location based social networks. 34th IEEE International Conference on Data Engineering (ICDE 2018), Paris, France, 16-19 April 2018. NEW YORK: IEEE. doi: 10.1109/ICDE.2018.00101

Lu, Lingjiao, Fang, Junhua, Zhao, Pengpeng, Xu, Jiajie, Yin, Hongzhi and Zhao, Lei (2018). Eliminating temporal conflicts in uncertain temporal knowledge graphs. 19th International Conference on Web Information Systems Engineering, WISE 2018, Dubai, United Arab Emirates, November 12 - 15, 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-02922-7_23

Wang, Qinyong, Yin, Hongzhi, Wang, Hao and Huang, Zi (2018). TSAUB: a temporal-sentiment-aware user behavior model for personalized recommendation. 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, 24-27 May 2018. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-92013-9_17

Qian, Qing, Li, Zhixu, Zhao, Pengpeng, Chen, Wei, Yin, Hongzhi and Zhao, Lei (2018). Publishing graph node strength histogram with edge differential privacy. 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, Gold Coast, QLD, Australia, 21-24 May 2018. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-91458-9_5

Zhao, Kangzhi, Zhang, Yong, Wang, Zihao, Yin, Hongzhi, Zhou, Xiaofang, Wang, Jin and Xing, Chunxiao (2018). Modeling patient visit using electronic medical records for cost profile estimation. 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, Gold Coast, QLD, Australia, 21-24 May 2018. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-91458-9_2

Yang, Jiali, Li, Zhixu, Yin, Hongzhi, Zhao, Pengpeng, Liu, An, Chen, Zhigang and Zhao, Lei (2018). Unified user and item representation learning for joint recommendation in social network. 19th International Conference on Web Information Systems Engineering, WISE 2018, Dubai, United Arab Emirates, November 12 - 15, 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-02925-8_3

Liu, Chunyang, Chen, Ling, Tsang, Ivor and Yin, Hongzhi (2018). Towards the Learning of Weighted Multi-label Associative Classifiers. 2018 International Joint Conference on Neural Networks, IJCNN 2018, Rio de Janeiro, Brazil, July 8 - 13, 2018. Institute of Electrical and Electronics Engineers. doi: 10.1109/IJCNN.2018.8489398

Wang, Weiqing, Yin, Hongzhi, Huang, Zi, Sun, Xiaoshuai and Hung, Nguyen Quoc Viet (2018). Restricted boltzmann machine based active learning for sparse recommendation. 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, Gold Coast, QLD Australia, 21 - 24 May 2018. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-91452-7_7

Zhou, Yiming, Han, Yuehui, Liu, An, Li, Zhixu, Yin, Hongzhi and Zhao, Lei (2018). Extracting representative user subset of social networks towards user characteristics and topological features. 19th International Conference on Web Information Systems Engineering, WISE 2018, Dubai, United Arab Emirates, November 12 - 15, 2018. Cham, Switzerland: Springer . doi: 10.1007/978-3-030-02922-7_15

Zhang, Chen, Du, Changying, Wang, Yijun, Yin, Hongzhi, Chen, Can and Wang, Hao (2018). Stock assistant: a stock AI assistant for reliability modeling of stock comments. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2018, London, United Kingdom, 19 - 23 August 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3219819.3219964

Zhang, Yan, Yin, Hongzhi, Huang, Zi, Du, Xingzhong, Yang, Guowu and Lian, Defu (2018). Discrete deep learning for fast content-aware recommendation. 11th ACM International Conference on Web Search and Data Mining, WSDM 2018, Marina Del Rey, CA, United States, 5-9 February 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3159652.3159688

Zhang, Yan, Wang, Haoyu, Lian, Defu, Tsang, Ivor W., Yin, Hongzhi and Yang, Guowu (2018). Discrete ranking-based matrix factorization with self-paced learning. 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), London, United Kingdom, 19 - 23 August 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3219819.3220116

Tam, Nguyen Thanh, Weidlich, Matthias, Zheng, Bolong, Yin, Hongzhi, Hung, Nguyen Quoc Viet and Stantic, Bela (2018). From anomaly detection to rumour detection using data streams of social platforms. 45th International Conference on Very Large Data Bases (VLDB 2019), Los Angeles, CA, United States, 26-30 August 2017. New York, NY, United States: Association for Computing Machinery (ACM). doi: 10.14778/3329772.3329778

Nguyen, Quoc Viet Hung, Huynh, Huu Viet, Nguyen, Thanh Tam, Weidlich, Matthias, Yin, Hongzhi and Zhou, Xiaofang (2018). Computing crowd consensus with partial agreement. 34th IEEE International Conference on Data Engineering (ICDE 2018), Paris, France, 16-19 April 2018. NEW YORK: IEEE. doi: 10.1109/ICDE.2018.00232

Chen, Tong, Li, Xue, Yin, Hongzhi and Zhang, Jun (2018). Call attention to rumors: deep attention based recurrent neural networks for early rumor detection. 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, Melbourne, VIC, Australia, 3 June 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-04503-6_4

Chen, Hongxu, Wang, Hao, Yin, Hongzhi, Nguyen, Quoc Viet Hung, Wang, Weiqing and Li, Xue (2018). PME: projected metric embedding on heterogeneous networks for link prediction. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2018, London, United Kingdom, 19 - 23 August 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3219819.3219986

Wang, Qinyong, Lian, Defu, Yin, Hongzhi, Wang, Hao, Hu, Zhiting and Huang, Zi (2018). Neural memory streaming recommender networks with adversarial training. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2018, London, United Kingdom, 19 - 23 August 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3219819.3220004

Wang, Weiqing, Yin, Hongzhi, Huang, Zi, Wang, Qinyong, Du, Xingzhong and Nguyen, Quoc Viet Hung (2018). Streaming ranking based recommender systems. 41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018, Ann Arbor, MI, United States, 8-12 July 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3209978.3210016

Lv, Zhongjian, Xu, Jiajie, Zheng, Kai, Yin, Hongzhi, Zhao, Pengpeng and Zhou, Xiaofang (2018). LC-RNN: A deep learning model for traffic speed prediction. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), Stockholm, Sweden, 13-19 July 2018. International Joint Conferences on Artificial Intelligence. doi: 10.24963/ijcai.2018/482

Sun, Yizhou, Yin, Hongzhi and Ren, Xiang (2017). Recommendation in context-rich environment: An information network analysis approach. 26th International World Wide Web Conference, WWW 2017 Companion, Perth, WA, Australia, April 3 - 7, 2017. Geneva, Switzerland: International World Wide Web Conferences Steering Committee. doi: 10.1145/3041021.3051105

Zheng, Wei, Li, Bohan, Wang, Yanan, Yin, Hongzhi, Li, Xue, Guan, Donghai and Qin, Xiaolin (2017). Group recommender model based on preference interaction. 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, Singapore, Singapore, 5–6 November 2017. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-69179-4_10

Sun, Xiaoshuai, Huang, Zi, Yin, Hongzhi and Shen, Heng Tao (2017). An integrated model for effective saliency prediction. 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, CA., United States, 04-10 February 2017. Palo Alto, CA., United States: AAAI press.

Wang, Hao , Fu, Yanmei , Wang, Qinyong , Yin, Hongzhi , Du, Changying and Xiong, Hui (2017). A location-sentiment-aware recommender system for both home-town and out-of-town users. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Halifax, NS, Canada, 13-17 August 2017. New York, NY, United States: ACM. doi: 10.1145/3097983.3098122

Xu, Yanxia, Huang, Jinjing, Liu, An, Li, Zhixu, Yin, Hongzhi and Zhao, Lei (2017). Time-constrained graph pattern matching in a large temporal graph. Joint Conference, APWeb-WAIM, Beijing, China, 7-9 July 2017. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-63579-8 9

Wang, Qinyong , Yin, Hongzhi and Wang, Hao (2017). A time and sentiment unification model for personalized recommendation. Joint Conference, APWeb-WAIM, Beijing, China, 7-9 July 2017. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-63564-4 8

Chen, Hongxu, Yin, Hongzhi, Li, Xue, Wang, Meng, Chen, Weitong and Chen, Tong (2017). People opinion topic model: opinion based user clustering in social networks. International Conference on World Wide Web Companion, Perth, Australia, 3-7 April 2017. Geneva, Switzerland: International World Wide Web Conferences Steering Committee. doi: 10.1145/3041021.3051159

Li, Yongjun, Peng, You, Zhang, Zhen, Xu, Quanqing and Yin, Hongzhi (2017). Understanding the user display names across social networks. International Conference on World Wide Web Companion, Perth, Australia, 3-7 April 2017. Geneva, Switzerland: International World Wide Web Conferences Steering Committee. doi: 10.1145/3041021.3051146

Sun, Xiaoshuai, Huang, Zi, Yin, Hongzhi and Shen, Heng Tao (2017). An integrated model for effective saliency prediction. AAAI Conference on Artificial Intelligence, San Francisco, CA, United States, 4-9 February 2017. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence.

Huang, Jinjing, Lin, Tianqiao, Liu, An, Li, Zhixu, Yin, Hongzhi and Zhao, Lei (2017). Influenced nodes discovery in temporal contact network. 18th International Conference on Web Information Systems Engineering, WISE 2017, Puschino, Russia, 7-11 October 2017. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-68783-4_32

Xie, Min, Yin, Hongzhi, Xu, Fanjiang, Wang, Hao and Zhou, Xiaofang (2017). Graph-based metric embedding for next POI recommendation. 17th International Conference on Web Information Systems Engineering (WISE), Shanghai, China, 8 - 10 November 2016. Heidelberg, Germany: Springer . doi: 10.1007/978-3-319-48743-4_17

Chen, Wei, Yin, Hongzhi, Wang, Weiqing, Zhao, Lei, Hua, Wen and Zhou, Xiaofang (2017). Exploiting spatio-temporal user behaviors for user linkage. 26th ACM International Conference on Information and Knowledge Management, CIKM 2017, Singapore, Singapore, 06 - 10 November 2017. New York, New York, United States: Association for Computing Machinery. doi: 10.1145/3132847.3132898

Tam, Nguyen Thanh, Weidlich, Matthias, Thang, Duong Chi, Yin, Hongzhi and Hung, Nguyen Quoc Viet (2017). Retaining data from streams of social platforms with minimal regret. International Joint Conference on Artificial Intelligence, IJCAI, Melbourne, Australia, 19-25 August 2017. Melbourne, Australia: International Joint Conferences on Artificial Intelligence. doi: 10.24963/ijcai.2017/397

Yin, Hongzhi, Chen, Hongxu, Sun, Xiaoshuai, Wang, Hao, Wang, Yang and Nguyen, Quoc Viet Hung (2017). SPTF: A scalable probabilistic tensor factorization model for semantic-aware behavior prediction. 17th IEEE International Conference on Data Mining, ICDM 2017, New Orleans, LA, USA, November 18-21, 2017. New York, USA: Institute of Electrical and Electronics Engineers . doi: 10.1109/ICDM.2017.68

Yin, Hongzhi, Chen, Liang, Wang, Weiqing, Du, Xingzhong, Nguyen, Quoc Viet Hung and Zhou, Xiaofang (2017). Mobi-SAGE: A sparse additive generative model for mobile app recommendation. IEEE 33rd International Conference on Data Engineering (ICDE), San Diego, CA, United States, 19-22 April 2017. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDE.2017.43

Hosseini, Saeid, Yin, Hongzhi, Zhang, Meihui, Zhou, Xiaofang and Sadiq, Shazia (2017). Jointly modeling heterogeneous temporal properties in location recommendation. 22nd Internation Conference, DASFAA 2017, Suzhou, China, 27 - 30 March 2017. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-55753-3_31

Yin, Hongzhi, Hu, Zhiting, Zhou, Xiaofang, Wang, Hao, Zheng, Kai, Quoc Viet Hung Nguyen and Sadiq, Shazia (2016). Discovering interpretable geo-social communities for user behavior prediction. IEEE International Conference on Data Engineering (ICDE), Helsinki, Finland, 16-20 May 2016. Washington, DC United States: IEEE Computer Society. doi: 10.1109/ICDE.2016.7498303

Xie, Min, Yin, Hongzhi, Wang, Hao, Xu, Fanjiang, Chen, Weitong and Wang, Sen (2016). Learning graph-based POI embedding for location-based recommendation. 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, United States, 24 - 28 October 2016. New York, NY, United States: ACM. doi: 10.1145/2983323.2983711

Du, Xingzhong, Yin, Hongzhi, Huang, Zi, Yang, Yi and Zhou, Xiaofang (2016). Using detected visual objects to index video database. Australasian Database Conference on Databases Theory and Applications, Sydney, Australia, 28-29 September 2016. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-46922-5_26

Zhao, Meng, Wang, Hao, Cao, Liangliang, Zhang, Chen, Yin, Hongzhi and Xu, Fanjiang (2016). LSIF: a system for large-scale information flow detection based on topic-related semantic similarity measurement. 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Singapore, 6-9 December 2016. Los Alamitos, CA United States: IEEE Computer Society. doi: 10.1109/WI-IAT.2015.2

Wang, Hao, Zhang, Chen, Yin, Hongzhi, Wang, Wei, Zhang, Jun and Xu, Fanjiang (2016). A unified framework for fine-grained opinion mining from online reviews. 49th Annual Hawaii International Conference on System Sciences, HICSS 2016, Koloa, HI, 5-8 January 2016. Piscataway, NJ, United States: I E E E. doi: 10.1109/HICSS.2016.144

Wang, Weiqing, Yin, Hongzhi, Sadiq, Shazia, Chen, Ling, Xie, Min and Zhou, Xiaofang (2016). SPORE: a sequential personalized spatial item recommender system. IEEE International Conference on Data Engineering (ICDE), Helsinki, Finland, 16-20 May 2016. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/ICDE.2016.7498304

Zheng, Bolong, Zheng, Kai, Xiao, Xiaokui, Su, Han, Yin, Hongzhi, Zhou, Xiaofang and Li, Guohui (2016). Keyword-aware continuous kNN query on road networks. IEEE International Conference on Data Engineering (ICDE), Helsinki, Finland, 16-20 May 2016. Washington, DC United States: IEEE Computer Society. doi: 10.1109/ICDE.2016.7498297

Yin, Hongzhi, Cui, Bin, Lu, Hua and Zhao, Lei (2016). Expert team finding for review assignment. Conference on Technologies and Applications of Artificial Intelligence (TAAI), Hsinchu, Taiwan, 25-27 November 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/TAAI.2016.7932314

Yin, Hongzhi, Cui, Bin, Huang, Zi, Wang, Weiqing, Wu, Xian and Zhou, Xiaofang (2015). Joint modeling of users' interests and mobility patterns for point-of-interest recommendation. 23rd ACM International Conference on Multimedia, MM 2015, Brisbane, QLD, Australia, 26-30 October, 2015. New York, NY, United States: Association for Computing Machinery, Inc. doi: 10.1145/2733373.2806339

He, Tieke, Yin, Hongzhi, Chen, Zhenyu, Zhou, Xiaofang and Luo, Bin (2015). Predicting users' purchasing behaviors using their browsing history. 26th Australasian Database Conference (ADC), Melbourne, Australia, 4-7 June 2015. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-19548-3_11

Dou, Mengyu, He, Tieke, Yin, Hongzhi, Zhou, Xiaofang, Chen, Zhenyu and Luo, Bin (2015). Predicting passengers in public transportation using smart card data. 26th Australasian Database Conference (ADC), Melbourne Australia, 4-7 June 2015. Heidelberg, Germany: Springer. doi: 10.1007/978-3-319-19548-3_3

Wu, Huimin, Shao, Jie, Yin, Hongzhi, Shen, Heng Tao and Zhou, Xiaofang (2015). Geographical constraint and temporal similarity modeling for point-of-interest recommendation. International Conference on Web Information Systems Engineering, Miami, FL, United States, 1-3 November 2015. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-26187-4_40

Xie, Yiran, Yin, Hongzhi, Cui, Bin, Yao, Junjie and Xu, Quanqing (2015). Distinguishing re-sharing behaviors from re-creating behaviors in information diffusion. 31st IEEE International Conference on Data Engineering Workshops 2015, Seoul, South Korea, 13-17 April 2015. IEEE Computer Society. doi: 10.1109/ICDEW.2015.7129573

Xu, Yanxia, Liu, Guanfeng, Yin, Hongzhi, Xu, Jiajie, Zheng, Kai and Zhao, Lei (2015). Discovering Organized POI Groups in a city. 20th International Conference on Database Systems for Advanced Applications (DASFAA), Hanoi, Vietnam, 20-23 April 2015. Heidelberg, Germany: Springer International Publishing. doi: 10.1007/978-3-319-22324-7_19

Wang, Weiqing, Yin, Hongzhi, Chen, Ling, Sun, Yizhou, Sadiq, Shazia and Zhou, Xiaofang (2015). Geo-SAGE: a geographical sparse additive generative model for spatial item recommendation. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Sydney, NSW, Australia, 10-13 August 2015. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2783258.2783335

Yin, Hongzhi, Zhou, Xiaofang, Shao, Yingxia, Wang, Hao and Sadiq, Shazia (2015). Joint modeling of user check-in behaviors for point-of-interest recommendation. 24th ACM International Conference on Information and Knowledge Management, CIKM 2015, Melbourme, VIC, Australia, 19-23 October, 2015. New York , NY, United States: Association for Computing Machinery. doi: 10.1145/2806416.2806500

Yin, Hongzhi, Cui, Bin, Chen, Ling, Hu, Zhiting and Huang, Zi (2014). A temporal context-aware model for user behavior modeling in social media systems. 2014 ACM SIGMOD International Conference on Management of Data, SIGMOD 2014, Snowbird, UT United States, 22-27 June 2014. New York, NY United States: Association for Computing Machinery. doi: 10.1145/2588555.2593685

Yin, Hongzhi, Cui, Bin, Lu, Hua, Huang, Yuxin and Yao, Junjie (2013). A unified model for stable and temporal topic detection from social media data. International Conference on Data Engineering, Brisbane, Australia, 8-11 April 2013. Washington, DC, United States: I E E E Computer Society. doi: 10.1109/ICDE.2013.6544864

Chen, Chen, Yin, Hongzhi, Yao, Junjie and Cui, Bin (2013). TeRec: a temporal recommender system over tweet stream. VLDB2013: 39th International Conference on Very Large Data Bases, Riva del Garda, Trento, Italy, 26-30 August, 2013. New York, NY, USA: Association for Computing Machinery. doi: 10.14778/2536274.2536289

Yin, Hongzhi, Sun, Yizhou, Cui, Bin, Hu, Zhiting and Chen, Ling (2013). LCARS: a location-content-aware recommender system. 19th ACM SIGKDD Knowledge Discovery and Data Mining, Chicago, IL, United States, 11-14 August 2013. New York, NY, United States: ACM. doi: 10.1145/2487575.2487608

Yin, Hongzhi, Cui, Bin, Li, Jing, Yao, Junjie and Chen, Chen (2012). Challenging the long tail recommendation. 38th International Conference on Very Large Data Bases 2012, (VLDB 2012), Istanbul, Turkey, 27-31 August 2012. New York, NY United States: Association for Computing Machinery. doi: 10.14778/2311906.2311916

Yin, Hongzhi, Cui, Bin and Huang, Yuxin (2011). Finding a wise group of experts in social networks. ADMA 2011: 7th International Conference on Advanced Data Mining and Applications, Beijing, China, 17-19 December, 2011. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-25853-4_29

Areas of research

Data Science