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2023

Conference Publication

Continuous input embedding size search for recommender systems

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

Continuous input embedding size search for recommender systems

2023

Conference Publication

KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment

Wang, Lingzhi, Chen, Tong, Yuan, Wei, Zeng, Xingshan, Wong, Kam-Fai and Yin, Hongzhi (2023). KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment. 61st Annual Meeting of the Association for Computational Linguistics, Toronto, Canada, 9 - 14 July 2023. Stroudsburg, PA United States: Association for Computational Linguistics. doi: 10.18653/v1/2023.acl-long.740

KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment

2023

Journal Article

Spatial-temporal meta-path guided explainable crime prediction

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

Spatial-temporal meta-path guided explainable crime prediction

2023

Journal Article

Reinforcement learning-enhanced shared-account cross-domain sequential recommendation

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

Reinforcement learning-enhanced shared-account cross-domain sequential recommendation

2023

Journal Article

DeHIN: a decentralized framework for embedding large-scale heterogeneous information networks

Imran, Mubashir, Yin, Hongzhi, Chen, Tong, Huang, Zi and Zheng, Kai (2023). DeHIN: a decentralized framework for embedding large-scale heterogeneous information networks. IEEE Transactions on Knowledge and Data Engineering, 35 (4), 3645-3657. doi: 10.1109/TKDE.2022.3141951

DeHIN: a decentralized framework for embedding large-scale heterogeneous information networks

2023

Journal Article

Time-Aware Dynamic Graph Embedding for Asynchronous Structural Evolution

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

Time-Aware Dynamic Graph Embedding for Asynchronous Structural Evolution

2023

Journal Article

ReFRS: Resource-efficient Federated Recommender System for dynamic and diversified user preferences

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

ReFRS: Resource-efficient Federated Recommender System for dynamic and diversified user preferences

2023

Journal Article

Decentralized collaborative learning framework for next POI recommendation

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

Decentralized collaborative learning framework for next POI recommendation

2023

Journal Article

Uniting heterogeneity, inductiveness, and efficiency for graph representation learning

Chen, Tong, Yin, Hongzhi, Ren, Jie, Huang, Zi, Zhang, Xiangliang and Wang, Hao (2023). Uniting heterogeneity, inductiveness, and efficiency for graph representation learning. IEEE Transactions on Knowledge and Data Engineering, 35 (2), 2103-2117. doi: 10.1109/TKDE.2021.3100529

Uniting heterogeneity, inductiveness, and efficiency for graph representation learning

2023

Conference Publication

Mind the accessibility gap: explorations of the disabling marketplace

Previte, Josephine, Wang, Jie, Chen, Rocky, Zhao, Yimeng and Pini, Barbara (2023). Mind the accessibility gap: explorations of the disabling marketplace. ANZMAC 2023: Marketing for good, Dunedin, New Zealand, 4 - 6 December 2023. Dunedin, New Zealand: University of Otago.

Mind the accessibility gap: explorations of the disabling marketplace

2023

Journal Article

TinyAD: memory-efficient anomaly detection for time series data in industrial IoT

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, 20 (1), 824-834. doi: 10.1109/tii.2023.3254668

TinyAD: memory-efficient anomaly detection for time series data in industrial IoT

2023

Journal Article

Cost-effective synchrophasor data source authentication based on multiscale adaptive coupling correlation detrended analysis

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

Cost-effective synchrophasor data source authentication based on multiscale adaptive coupling correlation detrended analysis

2022

Conference Publication

Integrating APSIM and PROSAIL to improve prediction of crop traits in various situations from hyperspectral data using deep learning

Chen, Qiaomin, Zheng, Bangyou, Chen, Tong and Chapman, Scott (2022). Integrating APSIM and PROSAIL to improve prediction of crop traits in various situations from hyperspectral data using deep learning. 20th Agronomy Australia Conference, Toowoomba, QLD, Australia, 18-22 September 2022. Willow Grove, VIC Australia: Australian Society of Agronomy.

Integrating APSIM and PROSAIL to improve prediction of crop traits in various situations from hyperspectral data using deep learning

2022

Journal Article

Multiscale adaptive multifractal detrended fluctuation analysis-based source identification of synchrophasor data

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

Multiscale adaptive multifractal detrended fluctuation analysis-based source identification of synchrophasor data

2022

Conference Publication

Thinking inside The Box : Learning Hypercube Representations for Group Recommendation

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

Thinking inside The Box : Learning Hypercube Representations for Group Recommendation

2022

Conference Publication

Are Graph Augmentations Necessary? : Simple Graph Contrastive Learning for Recommendation

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

Are Graph Augmentations Necessary? : Simple Graph Contrastive Learning for Recommendation

2022

Journal Article

Integrating crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning

Chen, Qiaomin, Zheng, Bangyou, Chen, Tong and Chapman, Scott C. (2022). Integrating crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning. Journal of Experimental Botany, 73 (19), 6558-6574. doi: 10.1093/jxb/erac291

Integrating crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning

2022

Conference Publication

Uniting heterogeneity, inductiveness, and efficiency for graph representation learning (Extended Abstract)

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

Uniting heterogeneity, inductiveness, and efficiency for graph representation learning (Extended Abstract)

2022

Conference Publication

Accepted Tutorials at The Web Conference 2022

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

Accepted Tutorials at The Web Conference 2022

2022

Conference Publication

Unified question generation with continual lifelong learning

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

Unified question generation with continual lifelong learning