Representation Learning for Attributed Multiplex Heterogeneous Network

• 概
• 符号说明
• 各种定义
  • Heterogeneous network
  • Attributed network
  • Attributed multiplex network
• 代码

Cen Y., Zou X., Zhang J., Yang H., Zhou J. and Tang J. Representation learning for attributed multiplex heterogeneous network. KDD, 2019.

概

本文在 Attributed (结点带属性) Multiplex (两个结点间可能有多个关系, 边) Heterogeneous (异构) 图上进行讨论. 这里不会讨论方法, 只记录下这些定义.

符号说明

各种定义

Heterogeneous network

假设存在一 node 映射 \(\phi: \mathcal{V} \rightarrow \mathcal{O}\) 将结点映射为某个结点类型, 一 edge 映射 \(\psi: \mathcal{E} \rightarrow \mathcal{R}\) 将边映射为某个边类型.
\(G = (\mathcal{V}, \mathcal{E})\) 为一异构图若 \(|\mathcal{O}| + |\mathcal{R}| > 2\).

Attributed network

令 \(G = (\mathcal{V, E, A})\) 为一 attributed network, 若 \(\mathcal{A} = \{\mathbf{x}_i|v_i \in \mathcal{V}\}\) 赋予每个结点 \(v_i\) 以属性 \(\mathbf{x}_i\).

Attributed multiplex network

称 attributed network \(G = (\mathcal{V, E, A}), \mathcal{E}=\bigcup_{r \in \mathcal{R}} \mathcal{E}_r, |\mathcal{R}| > 1\) 为 attributed multiplex heterogeneous network.

代码

official