国防科技大学学报2025，Vol.47Issue(3)：1-9,9.DOI:10.11887/j.cn.202503001
面向多视图异构图的分层投影嵌入方法
Multi-view heterogeneous graph embedding method with hierarchical projection
摘要
Abstract
A self-supervised graph embedding approach based on hierarchical projection network called MeghenNet(multi-view heterogeneous graph projection network)was introduced to learn low-dimensional representations from multiple views.The concept of multiple-view heterogeneous graphs was defined to explicitly allow the model to simultaneously collect information from multiple data sources for modeling heterogeneous graphs.A hierarchical attention projection that involves a cross-relation projection to extract semantics information within each view was employed,followed by a cross-view projection to aggregate contextual information from other views.The mutual information loss function between each view embedding and the global embedding was computed to ensure the information consistency across views.Experimental results on several real-world datasets demonstrate that the proposed method outperforms state-of-the-art approaches when handling multi-view heterogeneous graphs.关键词
异构图嵌入/多视图异构图/图卷积/互信息Key words
heterogeneous graph embedding/multi-view heterogeneous graphs/graph convolutional/mutual information分类
计算机与自动化引用本文复制引用
郝韵致,郑铜亚,王新根,王新宇,宋明黎,陈纯,周春燕..面向多视图异构图的分层投影嵌入方法[J].国防科技大学学报,2025,47(3):1-9,9.基金项目
国家自然科学基金资助项目(61671233,61801208) （61671233,61801208）
国家部委基金资助项目(51304010206) （51304010206）
