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Incorporating prior knowledge from counterfactuals into knowledge graph reasoning 期刊论文
Knowledge-Based Systems, 2021, 卷号: 223, 期号: 223, 页码: TBA
作者:  Wang, Zikang;  Li, Linjing;  Zeng, Daniel;  Wu, Xiaofei
Adobe PDF(1353Kb)  |  收藏  |  浏览/下载：338/149  |  提交时间：2021/05/31
knowledge graph  multi-hop reasoning  counterfactual  
Using deep learning to predict the hand-foot-and-mouth disease of enterovirus A71 subtype in Beijing from 2011 to 2018 期刊论文
SCIENTIFIC REPORTS, 2020, 卷号: 10, 期号: 1, 页码: 10
作者:  Wang, Yuejiao;  Cao, Zhidong;  Zeng, Daniel;  Wang, Xiaoli;  Wang, Quanyi
Adobe PDF(1497Kb)  |  收藏  |  浏览/下载：239/52  |  提交时间：2020/09/07
A topic enhanced approach to detecting multiple standpoints in web texts 期刊论文
INFORMATION SCIENCES, 2019, 卷号: 501, 页码: 483-494
作者:  Lin, Junjie;  Kong, Qingchao;  Mao, Wenji;  Wang, Lei
浏览  |  Adobe PDF(1004Kb)  |  收藏  |  浏览/下载：339/93  |  提交时间：2019/10/08
Multiple standpoint detection  Topic model  Topic enhanced approach  Adaptive parameter determination  
Unsupervised Semantic-Based Aggregation of Deep Convolutional Features 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 2, 页码: 601-611
作者:  Xu, Jian;  Wang, Chunheng;  Qi, Chengzuo;  Shi, Cunzhao;  Xiao, Baihua
浏览  |  Adobe PDF(1963Kb)  |  收藏  |  浏览/下载：390/89  |  提交时间：2019/07/12
Unsupervised  semantic-based aggregation  semantic detectors  
HiWalk: Learning node embeddings from heterogeneous networks 期刊论文
INFORMATION SYSTEMS, 2019, 卷号: 81, 期号: 1, 页码: 82-91
作者:  Bai, Jie;  Li, Linjing;  Zeng, Daniel
浏览  |  Adobe PDF(776Kb)  |  收藏  |  浏览/下载：373/75  |  提交时间：2019/07/12
Network analysis  Representation learning  Behavioral analysis  Random walk  Heterogeneous network  
Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-Scale Image Retrieval 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 卷号: 21, 期号: 6, 页码: 1551-1562
作者:  Xu, Jian;  Wang, Chunheng;  Qi, Chengzuo;  Shi, Cunzhao;  Xiao, Baihua
浏览  |  Adobe PDF(4727Kb)  |  收藏  |  浏览/下载：363/78  |  提交时间：2019/07/11
Iterative manifold embedding layer  image retrieval  incomplete data