MetaHGNIE: Novel Contrastive Learning for Heterogeneous Knowledge Graphs

This article introduces a new contrastive learning method, MetaHGNIE, for heterogeneous knowledge graphs. The focus on meta-path induced hypergraphs suggests a novel approach to capturing complex relationships within the data.

• •MetaHGNIE proposes a new contrastive learning method.
• •The method leverages meta-paths for knowledge graph analysis.
• •It targets heterogeneous knowledge graphs.