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2021 Journal Article Scalable robust graph embedding with SparkDuong, 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 |
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2021 Journal Article Towards Revenue Maximization with Popular and Profitable ProductsGan, 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 |
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2021 Conference Publication Self-supervised graph co-training for session-based recommendationCui, 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 |
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2021 Conference Publication A knowledge-aware recommender with attention-enhanced dynamic convolutional networkLiu, 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 |
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2021 Conference Publication Lightweight self-attentive sequential recommendationLi, 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 |
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2021 Conference Publication Double-scale self-supervised hypergraph learning for group recommendationZhang, 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 |
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2021 Conference Publication International Workshop on Privacy, Security and Trust in Computational Intelligence (PSTCI2021)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 |
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2021 Conference Publication GDFM: Gene Vectors Embodied Deep Attentional Factorization Machines for Interaction predictionMansha, 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 |
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2021 Journal Article Quaternion factorization machines: a lightweight solution to intricate feature interaction modelingChen, 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 |
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2021 Conference Publication Joint-teaching: learning to refine knowledge for resource-constrained unsupervised cross-modal retrievalZhang, 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 |
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2021 Conference Publication CausalRec: causal inference for visual debiasing in visually-aware recommendationQiu, 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 |
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2021 Journal Article Fast-adapting and privacy-preserving federated recommender systemWang, 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 |
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2021 Journal Article A block-based generative model for attributed network embeddingLiu, 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 |
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2021 Conference Publication ImGAGN: imbalanced network embedding via generative adversarial graph networksQu, 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 |
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2021 Conference Publication Learning elastic embeddings for customizing on-device recommendersChen, 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 |
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2021 Conference Publication Socially-aware self-supervised tri-training for recommendationYu, 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 |
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2021 Conference Publication Pre-training graph neural networks for cold-start users and items representationHao, 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 |
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2021 Conference Publication Temporal meta-path guided explainable recommendationChen, 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 |
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2021 Conference Publication Heterogeneous hypergraph embedding for graph classificationSun, 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 |
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2021 Conference Publication Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentationLi, 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 |
