English(EN) Dynamic Heterogeneous Graph Representation Learning: A Survey

综述详细介绍了动态异构图表示学习的方法

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-07 04:00

本综述全面概述了动态异构图（DHGs）表示学习的方法。它提出了DHGs的统一定义，并将现有方法分为基于嵌入、基于图神经网络（GNN）和基于Transformer的模型。该论文还总结了应用、数据集和基准测试，并概述了该新兴领域的未来研究方向。 AI

影响为学习复杂、演化网络数据的表示方法提供了结构化概述。

排序理由该条目是关于机器学习特定领域的一篇综述。 [lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Huan Liu, Pengfei Jiao, Jie Yin, Hongjiang Chen, Zhidong Zhao · 2026-09-07 04:00

动态异构图表示学习：综述

arXiv:2609.04779v1 Announce Type: cross Abstract: Graph representation learning (GRL) serves as a canonical paradigm for modeling complex networks. However, real-world AI systems inherently manifest as evolving heterogeneous entities with complex interactions, posing significant …