arXiv Preprints
Unsupervised Representation Learning for Time Series: A Review
Qianwen Meng, Hangwei Qian, Yong Liu, Yonghui Xu, Zhiqi Shen, Lizhen Cui
arXiv:2308.01578, Aug. 2023
[Code & Data]
A Survey on Federated Recommendation Systems
Zehua Sun, Yonghui Xu, Yong Liu, Wei He, Yali Jiang, Fangzhao Wu, Lizhen Cui
arXiv:2301.00767, Dec. 2022
Minimalist and High-performance Conversational Recommendation with Uncertainty Estimation for User Preference
Yinan Zhang, Boyang Li, Yong Liu, Yuan You, Chunyan Miao
arXiv:2206.14468, Jun. 2022
Selected Conference & Journal Papers
2023
[CIKM’23] Adaptive Multi-Modalities Fusion in Sequential Recommendation Systems
Hengchang Hu, Wei Guo, Yong Liu, Min-Yen Kan
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, Accepted, Oct. 21-25, 2023
[CIKM’23] DFFM: Domain Facilitated Feature Modeling for CTR Prediction
Wei Guo, Chenxu Zhu, Fan Yan, Bo Chen, Weiwen Liu, Huifeng Guo, Hongkun Zheng, Yong Liu, Ruiming Tang
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, Accepted, Oct. 21-25, 2023
[CIKM’23] APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation
Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, Accepted, Oct. 21-25, 2023
[Bioinformatics] KR4SL: Knowledge Graph Reasoning for Explainable Prediction of Synthetic Lethality
Ke Zhang, Min Wu, Yong Liu, Yimiao Feng, Jie Zheng
Bioinformatics, Volume 39, Issue Supplement_1, Pages i158–i167, Jun. 2023
[Code & Data]
[TNNLS] A Survey on Reinforcement Learning for Recommender Systems
Yuanguo Lin, Yong Liu, Fan Lin, Lixin Zou, Pengcheng Wu, Wenhua Zeng, Huanhuan Chen, Chunyan Miao
IEEE Transactions on Neural Networks and Learning Systems, Accepted, May 2023
[TNNLS] Multi-Component Adversarial Domain Adaptation: A General Framework
Changan Yi, Haotian Chen, Yonghui Xu, Huanhuan Chen, Yong Liu, Haishu Tan, Yugang Yan, Han Yu
IEEE Transactions on Neural Networks and Learning Systems, Accepted, Apr. 2023
[WWW’23] Bootstrap Latent Representations for Multi-modal Recommendation
Xin Zhou, Hongyu Zhou, Yong Liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You, Feijun Jiang
Proceedings of the ACM Web Conference 2023. Pages 845-854, Apr. 30 - May 4, 2023
[Code & Data]
[ICDE’23] Layer-refined Graph Convolutional Networks for Recommendation
Xin Zhou, Donghui Lin, Yong Liu, Chunyan Miao
Proceedings of the 39th IEEE International Conference on Data Engineering, Accepted, Apr. 3-7, 2023
[Code & Data]
[ICDE’23] Cross-Domain Disentangled Learning for E-Commerce Live Streaming Recommendation
Yixin Zhang, Yong Liu, Hao Xiong, Yi Liu, Fuqiang Yu, Wei He, Yonghui Xu, Lizhen Cui, Chunyan Miao
Proceedings of the 39th IEEE International Conference on Data Engineering, Accepted, Apr. 3-7, 2023
[ICDE’23] Delivery Time Prediction Using Large-Scale Graph Structure Learning Based on Quantile Regression
Lei Zhang, Xin Zhou, Yiming Cao, Yonghui Xu, Mingliang Wang, Xingyu Wu, Yong Liu, Lizhen Cui, Zhiqi Shen
Proceedings of the 39th IEEE International Conference on Data Engineering, Accepted, Apr. 3-7, 2023
[TORS] SELFCF: A Simple Framework for Self-supervised Collaborative Filtering
Xin Zhou, Aixin Sun, Yong Liu, Jie Zhang, Chunyan Miao
ACM Transactions on Recommender Systems, Accepted, Mar. 2023
[Code & Data]
[WSDM’23] Inductive Graph Transformer for Delivery Time Estimation
Xin Zhou, Jinglong Wang, Yong Liu, Xingyu Wu, Zhiqi Shen, Cyril Leung
Proceedings of the 16th ACM International Conference on Web Search and Data Mining. Pages 679-687. Feb. 27-Mar. 3, 2023
[AAAI’23] Revisiting Item Promotion in GNN-based Collaborative Filtering: A Masked Targeted Topological Attack Perspective
Yongwei Wang, Yong Liu, Zhiqi Shen
Proceedings of the 37th AAAI Conference on Artificial Intelligence, Accepted, Feb. 7-14, 2023
[AAAI’23] Next POI Recommendation with Dynamic Graph and Explicit Dependency
Feiyu Yin, Yong Liu, Zhiqi Shen, Lisi Chen, Shuo Shang, Peng Han
Proceedings of the 37th AAAI Conference on Artificial Intelligence, Accepted, Feb. 7-14, 2023
[AAAI’23] MHCCL: Masked Hierarchical Cluster-wise Contrastive Learning for Multivariate Time Series
Qianwen Meng, Hangwei Qian, Yong Liu, Lizhen Cui, Yonghui Xu, Zhiqi Shen
Proceedings of the 37th AAAI Conference on Artificial Intelligence, Accepted, Feb. 7-14, 2023
[Code & Data]
[TETCI] Dynamic Multi-objective Optimization Framework with Interactive Evolution for Sequential Recommendation
Wei Zhou, Yong Liu, Min Li, Yu Wang, Zhiqi Shen, Liang Feng, Zexuan Zhu
IEEE Transactions on Emerging Topics in Computational Intelligence, Accepted, Feb. 2023
2022
[EMNLP’22] History-aware Hierarchical Transformer for Multi-session Open-domain Dialogue System
Tong Zhang, Yong Liu, Boyang Li, Zhiwei Zeng, Pengwei Wang, Yuan You, Chunyan Miao, Lizhen Cui
Findings of the Association for Computational Linguistics: EMNLP 2022. Pages 3395-3407. Dec. 7-11, 2022
[TKDE] Aspect-guided Syntax Graph Learning for Explainable Recommendation
Yidan Hu, Yong Liu, Chunyan Miao, Gongqi Lin, Yuan Miao
IEEE Transactions on Knowledge and Data Engineering, Accepted, Oct. 2022
[CIKM’22] Memory Bank Augmented Long-tail Sequential Recommendation
Yidan Hu, Yong Liu, Chunyan Miao, Yuan Miao
Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Pages 791-801. Oct. 17-21, 2022
[Code & Data]
[Bioinformatics] NSF4SL: Negative-sample-free Contrastive Learning for Ranking Synthetic Lethal Partner Genes in Human Cancers
Shike Wang, Yimiao Feng, Xin Liu, Yong Liu, Min Wu, Jie Zheng
Bioinformatics, Volume 38, Issue Supplement_2, Pages ii13–ii19, Sep. 2022
[Code & Data]
[KDD’22] Graph-Flashback Network for Next Location Recommendation
Xuan Rao, Lisi Chen, Yong Liu, Shuo Shang, Bin Yao, Peng Han
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Pages 1463-1471. Aug. 14-18, 2022
[Code & Data]
[IJCAI’22] Enhancing Sequential Recommendation with Graph Contrastive Learning
Yixin Zhang, Yong Liu, Yonghui Xu, Hao Xiong, Chenyi Lei, Wei He, Lizhen Cui, Chunyan Miao
Proceedings of the 31st International Joint Conference on Artificial Intelligence. Pages 2398-2405. Jul. 23-29, 2022
[Code & Data]
[DASFAA’22] Diffusion-based Graph Contrastive Learning for Recommendation with Implicit Feedback
Lingzi Zhang, Yong Liu, Xin Zhou, Chunyan Miao, Guoxin Wang, Haihong Tang
Proceedings of the 27th International Conference on Database Systems for Advanced Applications. Pages 232–247. Apr. 11-14, 2022
[Code & Data]
[Bioinformatics] Pre-training Graph Neural Networks for Link Prediction in Biomedical Networks
Yahui Long, Min Wu, Yong Liu, Yuan Fang, Jinmiao Chen, Chee Keong Kwoh, Jiawei Luo, Xiaoli Li
Bioinformatics, Volume 38, Issue 8, Pages 2254–2262, Apr. 2022
[Code & Data]
[AEI] Heterogeneous Star Graph Attention Network for Product Attributes Prediction
Xuejiao Zhao, Yong Liu, Yonghui Xu, Yonghua Yang, Xusheng Luo, Chunyan Miao
Advanced Engineering Informatics, Volume 51, Jan. 2022
[Code & Data]
2021
[CIKM’21] Unsupervised Categorical Representation Learning for Package Arrival Time Prediction
Yang Li, Xingyu Wu, Jinglong Wang, Yong Liu, Xiaoqing Wang, Yuming Deng, Chunyan Miao
Proceedings of the 30th ACM International Conference on Information and Knowledge Management. Pages 3935-3944. Nov. 1-5, 2021
[CIKM’21] The Skyline of Counterfactual Explanations for Machine Learning Decision Models
Yongjie Wang, Qinxu Ding, Ke Wang, Yue Liu, Xingyu Wu, Jinglong Wang, Yong Liu, Chunyan Miao
Proceedings of the 30th ACM International Conference on Information and Knowledge Management. Pages 2030–2039. Nov. 1-5, 2021
[Code & Data]
[MM’21] Pre-training Graph Transformer with Multimodal Side Information for Recommendation
Yong Liu, Susen Yang, Chenyi Lei, Guoxin Wang, Haihong Tang, Juyong Zhang, Aixin Sun, Chunyan Miao
Proceedings of the 29th ACM International Conference on Multimedia (Oral). Pages 2853-2861. Oct. 20-24, 2021
[Code & Data]
[MM’21] Understanding Chinese Video and Language via Contrastive Multimodal Pre-Training
Chenyi Lei, Shixian Luo, Yong Liu, Wanggui He, Jiamang Wang, Guoxin Wang, Haihong Tang, Chunyan Miao, Houqiang Li
Proceedings of the 29th ACM International Conference on Multimedia. Pages 2567-2576. Oct. 20-24, 2021
[Bioinformatics] Graph Contextualized Attention Network for Predicting Synthetic Lethality in Human Cancers
Yahui Long, Min Wu, Yong Liu, Jie Zheng, Kwoh Chee Kong, Jiawei Luo, Xiaoli-Li
Bioinformatics, Volume 37, Issue 16, Pages 2432–2440, Aug. 2021
[Code & Data]
[KDD’21] SEMI: A Sequential Multi-Modal Information Transfer Network for E-Commerce Micro-Video Recommendations
Chenyi Lei, Yong Liu, Lingzi Zhang, Guoxin Wang, Haihong Tang, Houqiang Li, Chunyan Miao
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Pages 3161–3171. Aug. 14-18, 2021
[KDD’21] Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems
Yinan Zhang, Boyang Li, Yong Liu, Hao Wang, Chunyan Miao
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Pages 2263–2273. Aug. 14-18, 2021
[Code & Data]
[Bioinformatics] KG4SL: Knowledge Graph Neural Network for Synthetic Lethality Prediction in Human Cancers
Shike Wang, Fan Xu, Yunyang Li, Jie Wang, Ke Zhang, Yong Liu, Min Wu, Jie Zheng
Bioinformatics, Volume 37, Issue Supplement_1, Pages i418–i425, Jul. 2021
[Code & Data]
[TKDE] Neighbor-Anchored Adversarial Graph Neural Networks
Zemin Liu, Yuan Fang, Yong Liu, Vincent W. Zheng
IEEE Transactions on Knowledge and Data Engineering, Accepted, May 2021
[Code & Data]
[TKDE] Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph
Yong Liu, Susen Yang, Yonghui Xu, Chunyan Miao, Min Wu, Juyong Zhang
IEEE Transactions on Knowledge and Data Engineering, Accepted, May 2021
[Code & Data]
[TKDE] Learning Hierarchical Review Graph Representation for Recommendation
Yong Liu, Susen Yang, Yinan Zhang, Chunyan Miao, Zaiqing Nie, Juyong Zhang
IEEE Transactions on Knowledge and Data Engineering, Accepted, Apr. 2021
[Code & Data]
[AAAI’21] A Hybrid Bandit Framework for Diversified Recommendation
Qinxu Ding, Yong Liu, Chunyan Miao, Fei Cheng, Haihong Tang
Proceedings of the 35th AAAI Conference on Artificial Intelligence. Pages 4036-4044. Feb. 2-9, 2021
[AAAI’21] Keyword-Guided Neural Conversational Model
Peixiang Zhong, Yong Liu, Hao Wang, Chunyan Miao
Proceedings of the 35th AAAI Conference on Artificial Intelligence. Pages 14568-14576. Feb. 2-9, 2021
[Code & Data]
2020 and Before
[IJCAI’20] Learning Personalized Itemset Mapping for Cross-Domain Recommendation
Yinan Zhang, Yong Liu, Peng Han, Chunyan Miao, Lizhen Cui, Baoli Li, Haihong Tang
Proceedings of the 29th International Joint Conference on Artificial Intelligence. Pages 2561-2567. Jan. 7-15, 2021
[Code & Data]
[IJCAI’20] Contextualized Point-of-Interest Recommendation
Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, Shuo Shang
Proceedings of the 29th International Joint Conference on Artificial Intelligence. Pages 2484-2490. Jan. 7-15, 2021
[Code & Data]
[Bioinformatics] Ensembling graph attention networks for humanmicrobe-drug association prediction
Yahui Long, Min Wu, Yong Liu, Chee Keong Kwoh, Jiawei Luo, Xiao-li Li
Bioinformatics, Volume 36, Issue Supplement_2, Pages i779–i786, Dec. 2020
[Code & Data]
[EMNLP’20] Towards Persona-Based Empathetic Conversational Models
Peixiang Zhong, Chen Zhang, Hao Wang, Yong Liu, Chunyan Miao
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing. Pages 6556–6566. Nov. 16-20, 2020
[Code & Data]
[AAAI’20] Diversified Interactive Recommendation with Implicit Feedback
Yong Liu, Yingtai Xiao, Qiong Wu, Chunyan Miao, Juyong Zhang, Binqiang Zhao, Haihong Tang
Proceedings of the 34th AAAI Conference on Artificial Intelligence. Pages 4932-4939. New York, USA, Feb. 7-12, 2020
[IJCAI’19] PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation
Qiong Wu, Yong Liu, Chunyan Miao, Binqiang Zhao, Yin Zhao, Lu Guan
Proceedings of 28th International Joint Conference on Artificial Intelligence. Pages 3870-3876. Macao, China, Aug. 10-16, 2019
[Code & Data]
[KDD’19] GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization
Peng Han, Peng Yang, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, Panos Kalnis
Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Pages 705-713. Alaska, USA, Aug. 4-8, 2019
[Code & Data]
[IJCAI’18] Dynamic Bayesian Logistic Matrix Factorization for Recommendation with Implicit Feedback
Yong Liu, Lifan Zhao, Guimei Liu, Xinyan Lu, Peng Gao, Xiao-Li Li, Zhihui Jin
Proceedings of 27th International Joint Conference on Artificial Intelligence. Pages 3463-3469. Stockholm, Sweden, Jul. 13-19, 2018
[TCBB] SL2MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization
Yong Liu, Min Wu, Chenghao Liu, Xiao-Li Li, Jie Zheng
IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume 17, Issue 3, Pages 748–757, Apr. 2019
[Code & Data]
[SDM’18] Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback
Peng Yang, Peilin Zhao, Yong Liu, Xin Gao
Proceedings of 2018 SIAM International Conference on Data Mining. Pages 621-629. San Diego, California, USA, May 3-5, 2018
[IJCAI’17] Learning User Dependencies for Recommendation
Yong Liu, Peilin Zhao, Xin Liu, Min Wu, Lixin Duan, Xiao-Li Li
Proceedings of 26th International Joint Conference on Artificial Intelligence. Pages 2379-2385. Melbourne, Australia, Aug. 19-25, 2017
[IJCAI’17] Online Multitask Relative Similarity Learning
Shuji Hao, Peilin Zhao, Yong Liu, Steven C. H. Hoi, Chunyan Miao
Proceedings of 26th International Joint Conference on Artificial Intelligence. Pages 1823-1829. Melbourne, Australia, Aug. 19-25, 2017
[IJCAI’16] Exploring the Context of Locations for Personalized Location Recommendations
Xin Liu, Yong Liu, Xiao-Li Li
Proceedings of 25th International Joint Conference on Artificial Intelligence. Pages 1188-1194. New York City, USA, Jul. 9-16, 2016
[PLOS CB] Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction
Yong Liu, Min Wu, Chunyan Miao, Peilin Zhao, Xiao-Li Li
PLOS Computational Biology, Volume 12, Issue 2, e1004760, Feb. 2016
[Code & Data]
[IJCAI’15] A Boosting Algorithm for Item Recommendation with Implicit Feedback
Yong Liu, Peilin Zhao, Aixin Sun, Chunyan Miao
Proceedings of 24th International Joint Conference on Artificial Intelligence. Pages 1792-1798. Buenos Aires, Argentina, Jul. 25-31, 2015
[Code & Data]
[CIKM’14] Exploiting Geographical Neighborhood Characteristics for Location Recommendation
Yong Liu, Wei Wei, Aixin Sun, Chunyan Miao
Proceedings of 23rd ACM International Conference on Information and Knowledge Management. Pages 739-748. Shanghai, China, Nov. 3-7, 2014
[Code & Data]
[SIGIR’14] Your Neighbors Affect Your Ratings: On Geographical Neighborhood Influence to Rating Prediction
Longke Hu, Aixin Sun, Yong Liu
Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval. Pages 345-354. Gold Coast, Australia, Jul. 6-11, 2014
[CIKM’13] Personalized Point-of-Interest Recommendation by Mining Users’ Preference Transition
Xin Liu, Yong Liu, Karl Aberer, Chunyan Miao
Proceedings of 22nd ACM International Conference on Information and Knowledge Management. Pages 733-738. San Francisco, USA, Oct. 27-Nov. 1, 2013
Workshop Papers
[NLP4ConvAI’22] Toward Knowledge-Enriched Conversational Recommendation Systems
Tong Zhang, Yong Liu, Boyang Li, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao
Proceedings of the 4th Workshop on NLP for Conversational AI. Pages 212–217. May 27, 2022
[Code & Data]
Book Chapters
Classification of Travel Patterns Including Wandering Based on Bi-directional Long Short-Term Memory Networks
Nhu Khue Vuong, Yong Liu, Syin Chan, Chiew Tong Lau, Zhenghua Chen, Min Wu and Xiaoli Li
Generalization With Deep Learning: For Improvement On Sensing Capability, Edited by Zhenghua Chen, Min Wu, Xiaoli Li, ISBN: 978-981-121-885-9, World Scientific, April 2021
Matrix Factorization for Drug-Target Interaction Prediction
Yong Liu, Min Wu, Peilin Zhao, Xiao-Li Li
High Performance Computing for Big Data: Methodologies and Applications, Edited by Chao Wang, ISBN: 978-1498783996, CRC Press, October 2017
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