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Table 3 Summary of all notations

From: HNF-DDA: subgraph contrastive-driven transformer-style heterogeneous network embedding for drug–disease association prediction

Symbol

Description

Symbol

Description

\(G\)

Biomedical heterogeneous network

\(H\)

Feature Embedding Matrix

\(V\)

Heterogeneous network node set

\(t\)

Node type

\(E\)

Heterogeneous network edge set

\(W\)

Weight matrix

\(\mathcal{A}\)

Node attribute set

\(B\)

Bias matrix

\(\mathcal{R}\)

Node type set

\(d\)

Embedding feature dimensions

\(N\)

Number of nodes

\(z\)

Node embedding feature vector

\({v}_{i}\)

The \(i\) node of network

\(g\)

Sampled from Gumbel distribution

\({a}_{i}\)

Attribute feature of node \({v}_{i}\)

\(\mathcal{T}\)

Temperature coefficient

\(\tau (\bullet )\)

Node type mapping function

\(b\)

Learnable weight parameter

\(\sigma (\bullet )\)

Activation function

\(\phi \left(\bullet \right)\)

Positive Random Features (PRF)

\(\widehat{Y}\)

Predicted probability of the label

\(C\)

The intermediate node set

\(s\)

The ending node (disease/drug)

\(M\)

Subgraph node set