|
2018 Journal Article PrefaceZhou, Xiaofang and Yin, Hongzhi (2018). Preface. Journal of Computer Science and Technology, 33 (4), 621-624. doi: 10.1007/s11390-018-1844-1 |
|
2018 Journal Article A deep dive into user display names across social networksLi, Yongjun, Peng, You, Zhang, Zhen, Wu, Mingjie, Xu, Quanqing and Yin, Hongzhi (2018). A deep dive into user display names across social networks. Information Sciences, 447, 186-204. doi: 10.1016/j.ins.2018.02.072 |
|
2018 Journal Article Matching user accounts based on user generated content across social networksLi, Yongjun, Zhang, Zhen, Peng, You, Yin, Hongzhi and Xu, Quanqing (2018). Matching user accounts based on user generated content across social networks. Future Generation Computer Systems, 83, 104-115. doi: 10.1016/j.future.2018.01.041 |
|
2018 Journal Article Layered convolutional dictionary learning for sparse coding itemsetsMansha, Sameen, Lam, Hoang Thanh, Yin, Hongzhi, Kamiran, Faisal and Ali, Mohsen (2018). Layered convolutional dictionary learning for sparse coding itemsets. World Wide Web, 22 (5), 1-15. doi: 10.1007/s11280-018-0565-2 |
|
2018 Journal Article Matching user accounts across social networks based on username and display nameLi, Yongjun, Peng, You, Zhang, Zhen, Yin, Hongzhi and Xu, Quanqing (2018). Matching user accounts across social networks based on username and display name. World Wide Web, 22 (3), 1-23. doi: 10.1007/s11280-018-0571-4 |
|
2018 Journal Article User identity linkage across social networks via linked heterogeneous network embeddingWang, Yaqing, Feng, Chunyan, Chen, Ling, Yin, Hongzhi, Guo, Caili and Chu, Yunfei (2018). User identity linkage across social networks via linked heterogeneous network embedding. World Wide Web, 22 (6), 1-22. doi: 10.1007/s11280-018-0572-3 |
|
2018 Conference Publication PME: projected metric embedding on heterogeneous networks for link predictionChen, Hongxu, Wang, Hao, Yin, Hongzhi, Nguyen, Quoc Viet Hung, Wang, Weiqing and Li, Xue (2018). PME: projected metric embedding on heterogeneous networks for link prediction. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2018, London, United Kingdom, 19 - 23 August 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3219819.3219986 |
|
2018 Conference Publication Discrete ranking-based matrix factorization with self-paced learningZhang, Yan, Wang, Haoyu, Lian, Defu, Tsang, Ivor W., Yin, Hongzhi and Yang, Guowu (2018). Discrete ranking-based matrix factorization with self-paced learning. 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), London, United Kingdom, 19 - 23 August 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3219819.3220116 |
|
2018 Journal Article Computing crowd consensus with partial agreementViet Hung, Nguyen Quoc, Viet, Huynh Huu, Tam, Nguyen Thanh, Weidlich, Matthias, Yin, Hongzhi and Zhou, Xiaofang (2018). Computing crowd consensus with partial agreement. IEEE Transactions on Knowledge and Data Engineering, 30 (1), 1-14. doi: 10.1109/TKDE.2017.2750683 |
|
2018 Conference Publication Neural memory streaming recommender networks with adversarial trainingWang, Qinyong, Lian, Defu, Yin, Hongzhi, Wang, Hao, Hu, Zhiting and Huang, Zi (2018). Neural memory streaming recommender networks with adversarial training. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2018, London, United Kingdom, 19 - 23 August 2018. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3219819.3220004 |
|
2018 Conference Publication LC-RNN: A deep learning model for traffic speed predictionLv, Zhongjian, Xu, Jiajie, Zheng, Kai, Yin, Hongzhi, Zhao, Pengpeng and Zhou, Xiaofang (2018). LC-RNN: A deep learning model for traffic speed prediction. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), Stockholm, Sweden, 13-19 July 2018. FREIBURG: International Joint Conferences on Artificial Intelligence. doi: 10.24963/ijcai.2018/482 |
|
2018 Conference Publication User guidance for efficient fact checkingNguyen, Thanh Tam, Weidlich, Matthias, Yin, Hongzhi, Zheng, Bolong, Hung Nguyen, Quoc Viet and Stantic, Bela (2018). User guidance for efficient fact checking. 45th International Conference on Very Large Data Bases, Los Angeles, CA United States, 2019. New York, NY United States: Association for Computing Machinery. doi: 10.14778/3324301.3324303 |
|
2018 Conference Publication Mining subgraphs from propagation networks through temporal dynamic analysisHosseini, Saeid, Yin, Hongzhi, Zhang, Meihui, Elovici, Yuval and Zhou, Xiaofang (2018). Mining subgraphs from propagation networks through temporal dynamic analysis. 19th IEEE International Conference on Mobile Data Management, MDM 2018, Aalborg University, Aalborg, Denmark, 26-28 June 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/MDM.2018.00023 |
|
2018 Conference Publication Adaptive implicit friends identification over heterogeneous network for social recommendationYu, 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 |
|
2018 Conference Publication Towards the Learning of Weighted Multi-label Associative ClassifiersLiu, Chunyang, Chen, Ling, Tsang, Ivor and Yin, Hongzhi (2018). Towards the Learning of Weighted Multi-label Associative Classifiers. 2018 International Joint Conference on Neural Networks, IJCNN 2018, Rio de Janeiro, Brazil, July 8 - 13, 2018. Institute of Electrical and Electronics Engineers. doi: 10.1109/IJCNN.2018.8489398 |
|
2018 Conference Publication TADA: trend alignment with dual-attention multi-task recurrent neural networks for sales predictionChen, Tong, Yin, Hongzhi, Chen, Hongxu, Wu, Lin, Wang, Hao, Zhou, Xiaofang and Li, Xue (2018). TADA: trend alignment with dual-attention multi-task recurrent neural networks for sales prediction. 18th IEEE International Conference on Data Mining, ICDM 2018, Singapore, 17-20 November 2018. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/ICDM.2018.00020 |
|
2018 Conference Publication Exploiting reshaping subgraphs from bilateral propagation graphsHosseini, Saeid, Yin, Hongzhi, Cheung, Ngai-Man, Leng, Kan Pak, Elovici, Yuval and Zhou, Xiaofang (2018). Exploiting reshaping subgraphs from bilateral propagation graphs. 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, Gold Coast, QLD, Australia, 21-24 May 2018. Cham, Switzerland: Springer Verlag. doi: 10.1007/978-3-319-91452-7_23 |
|
2018 Conference Publication Computing crowd consensus with partial agreementNguyen, Quoc Viet Hung, Huynh, Huu Viet, Nguyen, Thanh Tam, Weidlich, Matthias, Yin, Hongzhi and Zhou, Xiaofang (2018). Computing crowd consensus with partial agreement. 34th IEEE International Conference on Data Engineering (ICDE 2018), Paris, France, 16-19 April 2018. NEW YORK: IEEE. doi: 10.1109/ICDE.2018.00232 |
|
2018 Conference Publication Look deeper see richer: Depth-aware image paragraph captioningWang, Ziwei, Luo, Yadan, Li, Yang, Huang, Zi and Yin, Hongzhi (2018). Look deeper see richer: Depth-aware image paragraph captioning. 26th ACM Multimedia conference, MM 2018, Seoul, South Korea, October 22 - 26, 2018. New York, NY, Untied States: Association for Computing Machinery, Inc. doi: 10.1145/3240508.3240583 |
|
2018 Book Chapter Spatiotemporal recommendation in geo-social networksYin, Hongzhi, Cui, Bin and Zhou, Xiaofang (2018). Spatiotemporal recommendation in geo-social networks. Encyclopedia of Social Network Analysis and Mining. (pp. 2930-2948) edited by Reda Alhajj and Jon Rokne. New York, NY, United States: Springer New York. doi: 10.1007/978-1-4939-7131-2_110177 |
