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2021

Conference Publication

Enhancing domain-level and user-level adaptivity in diversified recommendation

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

Enhancing domain-level and user-level adaptivity in diversified recommendation

2021

Conference Publication

Learning to ask appropriate questions in conversational recommendation

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

Learning to ask appropriate questions in conversational recommendation

2021

Journal Article

Utility mining across multi-dimensional sequences

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

Utility mining across multi-dimensional sequences

2021

Conference Publication

Self-supervised hypergraph convolutional networks for session-based recommendation

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.

Self-supervised hypergraph convolutional networks for session-based recommendation

2021

Conference Publication

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation

Xia, Xin, Yin, Hongzhi, Yu, Junliang, Wang, Qinyong, Cui, Lizhen and Zhang, Xiangliang (2021). Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Online, 2–9 February 2021. Washington, DC United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v35i5.16578

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation

2021

Conference Publication

Adapting to context-aware knowledge in natural conversation for multi-turn response selection

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

Adapting to context-aware knowledge in natural conversation for multi-turn response selection

2021

Conference Publication

Multi-level hyperedge distillation for social linking prediction on sparsely observed networks

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

Multi-level hyperedge distillation for social linking prediction on sparsely observed networks

2021

Conference Publication

Graph embedding for recommendation against attribute inference attacks

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

Graph embedding for recommendation against attribute inference attacks

2021

Conference Publication

Self-supervised multi-channel hypergraph convolutional network for social recommendation

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

Self-supervised multi-channel hypergraph convolutional network for social recommendation

2021

Conference Publication

DDHH: A decentralized deep learning framework for large-scale heterogeneous networks

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

DDHH: A decentralized deep learning framework for large-scale heterogeneous networks

2021

Conference Publication

Entity alignment for knowledge graphs with multi-order convolutional networks (extended abstract)

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

Entity alignment for knowledge graphs with multi-order convolutional networks (extended abstract)

2021

Conference Publication

Gallat: A spatiotemporal graph attention network for passenger demand prediction

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

Gallat: A spatiotemporal graph attention network for passenger demand prediction

2021

Conference Publication

Reliable recommendation with review-level explanations

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

Reliable recommendation with review-level explanations

2021

Journal Article

Disease prediction via graph neural networks

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

Disease prediction via graph neural networks

2021

Journal Article

An integrated model based on deep multimodal and rank learning for point-of-interest recommendation

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

An integrated model based on deep multimodal and rank learning for point-of-interest recommendation

2021

Journal Article

Efficient and effective multi-modal queries through heterogeneous network embedding

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

Efficient and effective multi-modal queries through heterogeneous network embedding

2021

Journal Article

Reinforced KGs reasoning for explainable sequential recommendation

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

Reinforced KGs reasoning for explainable sequential recommendation

2021

Journal Article

Efficient streaming subgraph isomorphism with graph neural networks

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

Efficient streaming subgraph isomorphism with graph neural networks

2021

Conference Publication

Subgraph convolutional network for recommendation

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

Subgraph convolutional network for recommendation

2021

Conference Publication

Recommending courses in MOOCs for jobs: an auto weak supervision approach

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

Recommending courses in MOOCs for jobs: an auto weak supervision approach