Mr Junliang Yu
Research Officer & Research Officer
School of Information Technology and Electrical Engineering
Researcher biography
Junliang Yu joined UQ as a Postdoctoral Research Fellow in January 2023. Prior to that, he completed his PhD degree at UQ, Master and Bachelor degrees at Chongqing University.
During his PhD, he published over 10 peer-reviewed papers in the most prestigious conferences including KDD, WWW, ICDM, AAAI, CIKM, and journals including TKDE, TOIS, and VLDBJ.
He works closely with Professor Shazia Sadiq and Associate Professor Hongzhi Yin.
Journal Articles
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
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. doi: 10.1145/3580364
Tao, Yinghui, Gao, Min, Yu, Junliang, Wang, Zongwei, Xiong, Qingyu and Wang, Xu (2022). Predictive and contrastive: dual-auxiliary learning for recommendation. IEEE Transactions on Computational Social Systems, PP (99), 1-12. doi: 10.1109/TCSS.2022.3185714
Wu, Fan, Gao, Min, Yu, Junliang, Wang, Zongwei, Liu, Kecheng and Wang, Xu (2021). Ready for emerging threats to recommender systems? A graph convolution-based generative shilling attack. Information Sciences, 578, 683-701. doi: 10.1016/j.ins.2021.07.041
Zhang, Junwei, Gao, Min, Yu, Junliang, Yang, Linda, Wang, Zongwei and Xiong, Qingyu (2021). Path-based reasoning over heterogeneous networks for recommendation via bidirectional modeling. Neurocomputing, 461, 438-449. doi: 10.1016/j.neucom.2021.07.038
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
Gao, Min, Zhang, Junwei, Yu, Junliang, Li, Jundong, Wen, Junhao and Xiong, Qingyu (2021). Recommender systems based on generative adversarial networks: A problem-driven perspective. Information Sciences, 546, 1166-1185. doi: 10.1016/j.ins.2020.09.013
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
Yu, Junliang, Gao, Min, Rong, Wenge, Song, Yuqi and Xiong, Qingyu (2017). A social recommender based on factorization and distance metric learning. IEEE Access, 5, 21557-21566. doi: 10.1109/access.2017.2762459
Conference Papers
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
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, 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
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
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
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
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.
Zhang, Junwei, Gao, Min, Yu, Junliang, Wang, Xinyi, Song, Yuqi and Xiong, Qingyu (2019). Nonlinear Transformation for Multiple Auxiliary Information in Music Recommendation. 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, 14-19 July 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IJCNN.2019.8851992
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
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