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2020 Conference Publication Multi-level graph convolutional networks for cross-platform Anchor Link PredictionChen, Hongxu, Yin, Hongzhi, Sun, Xiangguo, Chen, Tong, Gabrys, Bogdan and Musial, Katarzyna (2020). Multi-level graph convolutional networks for cross-platform Anchor Link Prediction. ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Virtual Event, CA, United States, 23-27 August 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3394486.3403201 |
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2020 Conference Publication GAG: global attributed graph neural network for streaming session-based recommendationQiu, Ruihong, Yin, Hongzhi, Huang, Zi and Chen, Tong (2020). GAG: global attributed graph neural network for streaming session-based recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China , 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401109 |
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2020 Conference Publication Try this instead: personalized and interpretable substitute recommendationChen, Tong, Yin, Hongzhi, Ye, Guanhua, Huang, Zi, Wang, Yang and Wang, Meng (2020). Try this instead: personalized and interpretable substitute recommendation. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China, 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401042 |
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2020 Conference Publication FactCatch: incremental pay-as-you-go fact checking with minimal user effortNguyen, Thanh Tam, Weidlich, Matthias, Yin, Hongzhi, Zheng, Bolong, Nguyen, Quang Huy and Nguyen, Quoc Viet Hung (2020). FactCatch: incremental pay-as-you-go fact checking with minimal user effort. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event China, 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401408 |
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2020 Conference Publication Discovering subsequence patterns for next POI recommendationZhao, Kangzhi, Zhang, Yong, Yin, Hongzhi, Wang, Jin, Zheng, Kai, Zhou, Xiaofang and Xing, Chunxiao (2020). Discovering subsequence patterns for next POI recommendation. Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20), Yokohama, Japan, 11-17 July, 2020. California, United States: International Joint Conferences on Artificial Intelligence Organization. doi: 10.24963/ijcai.2020/445 |
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2020 Journal Article TEAGS: time-aware text embedding approach to generate subgraphsHosseini, Saeid, Najafipour, Saeed, Cheung, Ngai-Man, Yin, Hongzhi, Kangavari, Mohammad Reza and Zhou, Xiaofang (2020). TEAGS: time-aware text embedding approach to generate subgraphs. Data Mining and Knowledge Discovery, 34 (4), 1136-1174. doi: 10.1007/s10618-020-00688-7 |
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2020 Journal Article User account linkage across multiple platforms with location dataChen, Wei, Wang, Weiqing, Yin, Hongzhi, Fang, Jun-Hua and Zhao, Lei (2020). User account linkage across multiple platforms with location data. Journal of Computer Science and Technology, 35 (4), 751-768. doi: 10.1007/s11390-020-0250-7 |
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2020 Journal Article Extracting representative user subset of social networks towards user characteristics and topological featuresZhou, Yiming, Han, Yuehui, Liu, An, Li, Zhixu, Yin, Hongzhi, Chen, Wei and Zhao, Lei (2020). Extracting representative user subset of social networks towards user characteristics and topological features. World Wide Web, 23 (5), 2903-2931. doi: 10.1007/s11280-020-00828-5 |
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2020 Journal Article Exploiting cross-session information for session-based recommendation with graph neural networksQiu, Ruihong, Huang, Zi, Li, Jingjing and Yin, Hongzhi (2020). Exploiting cross-session information for session-based recommendation with graph neural networks. ACM Transactions on Information Systems, 38 (3) 22, 1-23. doi: 10.1145/3382764 |
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2020 Journal Article Social boosted recommendation with folded bipartite network embeddingChen, Hongxu, Yin, Hongzhi, Chen, Tong, Wang, Weiqing, Li, Xue and Hu, Xia (2020). Social boosted recommendation with folded bipartite network embedding. IEEE Transactions on Knowledge and Data Engineering, 34 (2), 914-926. doi: 10.1109/tkde.2020.2982878 |
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2020 Journal Article Group-based recurrent neural networks for POI recommendationLi, Guohui, Chen, Qi, Zheng, Bolong, Yin, Hongzhi, Nguyen, Quoc Viet Hung and Zhou, Xiaofang (2020). Group-based recurrent neural networks for POI recommendation. ACM/IMS Transactions on Data Science, 1 (1) 3, 1-18. doi: 10.1145/3343037 |
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2020 Journal Article Cluster query: a new query pattern on temporal knowledge graphHuang, Jinjing, Chen, Wei, Liu, An, Wang, Weiqing, Yin, Hongzhi and Zhao, Lei (2020). Cluster query: a new query pattern on temporal knowledge graph. World Wide Web, 23 (2), 755-779. doi: 10.1007/s11280-019-00754-1 |
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2020 Journal Article Local variational feature-based similarity models for recommending top-N new itemsChen, Yifan, Wang, Yang, Zhao, Xiang, Yin, Hongzhi, Markov, Ilya and De Rijke, Maarten (2020). Local variational feature-based similarity models for recommending top-N new items. ACM Transactions on Information Systems, 38 (2) 12, 1-33. doi: 10.1145/3372154 |
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2020 Journal Article SGPM: a privacy protected approach of time-constrained graph pattern matching in cloudHuang, Jinjing, Chen, Wei, Li, Zhixu, Zhao, Pengpeng, Wang, Weiqing, Yin, Hongzhi and Zhao, Lei (2020). SGPM: a privacy protected approach of time-constrained graph pattern matching in cloud. World Wide Web-Internet and Web Information Systems, 23 (1), 519-547. doi: 10.1007/s11280-020-00784-0 |
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2020 Conference Publication Group recommendation with latent voting mechanismGuo, Lei, Yin, Hongzhi, Wang, Qinyong, Cui, Bin, Huang, Zi and Cui, Lizhen (2020). Group recommendation with latent voting mechanism. 2020 IEEE 36th International Conference on Data Engineering (ICDE), Dallas, TX, United States, 20-24 April 2020. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/ICDE48307.2020.00018 |
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2020 Conference Publication Where to go next: modeling long- and short-term user preferences for point-of-interest recommendationSun, Ke, Qian, Tieyun, Chen, Tong, Liang, Yile, Nguyen, Quoc Viet Hung and Yin, Hongzhi (2020). Where to go next: modeling long- and short-term user preferences for point-of-interest recommendation. AAAI Conference on Artificial Intelligence, New York, NY, United States, 7-12 February 2020. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v34i01.5353 |
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2020 Conference Publication Next point-of-interest recommendation on resource-constrained mobile devicesWang, Qinyong, Yin, Hongzhi, Chen, Tong, Huang, Zi, Wang, Hao, Zhao, Yanchang and Viet Hung, Nguyen Quoc (2020). Next point-of-interest recommendation on resource-constrained mobile devices. WWW '20: The Web Conference 2020, Taipei, Taiwan, April 2020. New York, United States: Association for Computing Machinery. doi: 10.1145/3366423.3380170 |
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2020 Conference Publication Neural pairwise ranking factorization machine for item recommendationJiao, Lihong, Yu, Yonghong, Zhou, Ningning, Zhang, Li and Yin, Hongzhi (2020). Neural pairwise ranking factorization machine for item recommendation. International Conference on Database Systems for Advanced Applications, Jeju, South Korea, 24-27 September 2020. Heidelberg, Germany: Springer . doi: 10.1007/978-3-030-59410-7_46 |
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2020 Journal Article Few-shot deep adversarial learning for video-based person re-identificationWu, Lin, Wang, Yang, Yin, Hongzhi, Wang, Meng and Shao, Ling (2020). Few-shot deep adversarial learning for video-based person re-identification. IEEE Transactions on Image Processing, 29 8839731, 1233-1245. doi: 10.1109/tip.2019.2940684 |
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2020 Conference Publication GCN-based user representation learning for unifying robust recommendation and fraudster detectionZhang, Shijie, Yin, Hongzhi, Chen, Tong, Hung, Quoc Viet Nguyen, Huang, Zi and Cui, Lizhen (2020). GCN-based user representation learning for unifying robust recommendation and fraudster detection. SIGIR '20: 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Online, July 2020. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3397271.3401165 |
