openhgnn.models.MHNF

class MHNF(num_edge_type, num_channels, in_dim, hidden_dim, num_class, num_layers, category, norm, identity)[源代码]

MHNF from paper Multi-hop Heterogeneous Neighborhood information Fusion graph representation learning.

Given a heterogeneous graph \(G\) and its edge relation type set \(\mathcal{R}\).Then we can extract l-hops hybrid adjacency matrix list in HMAE model. The hybrid adjacency matrix list can be used in HLHIA model to generate l-hops representations. Then HSAF model use attention mechanism to aggregate l-hops representations and because of multi-channel conv, the HSAF model also aggregates different channels l-hops representations to generate a final representation. You can see detail operation in correspond model.

参数:

  • num_edge_type (int) – Number of relations.

  • num_channels (int) – Number of conv channels.

  • in_dim (int) – The dimension of input feature.

  • hidden_dim (int) – The dimension of hidden layer.

  • num_class (int) – Number of classification type.

  • num_layers (int) – Length of hybrid metapath.

  • category (string) – Type of predicted nodes.

  • norm (bool) – If True, the adjacency matrix will be normalized.

  • identity (bool) – If True, the identity matrix will be added to relation matrix set.