Knowledge graph embedding (KGE) is a task to transform the symbolic entities and relations in Knowledge Graphs(KGs) into low-dimensional vectors, which facilitates the use of KGs in downstream applications. However, most existing models ignore the semantic correlations among similar entities and ...
作者:Guangyu Huo, Yong Zhang, Junbin Gao, Boyue Wang, Yongli Hu, Baocai Yin 发表时间:2021年1月 论文地址: 目录 论文阅读06——《CaEGCN: Cross-Attention Fusion based Enhanced Graph Convolutional Network for Clustering》 Ideas: Model: 交叉注意力融合模块 图自编码器 Ideas: 提出一种基于端到端的交...
Learning robust affinity graph representation for multi-view clustering Inform. Sci. (2021) ChangS. et al. Multi-view clustering via deep concept factorization Knowl.-Based Syst. (2021) LiH. et al. Robust energy preserving embedding for multi-view subspace clustering Knowl.-Based Syst. (2020) ...
Fast semi-supervised clustering with enhanced spectral embedding. Pattern Recognit. 2012, 45, 4358–4369. [Google Scholar] [CrossRef] Kim, T.H.; Lee, K.M.; Lee, S.U. Learning full pairwise affinities for spectral segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 2013, 35, 1690–...