Edge: Enriching Knowledge Graph Embeddings with External Text

Understand

Knowledge graphs suffer from sparsity which degrades the quality of representations generated by various methods.

• While there is an abundance of textual information throughout the web and many existing knowledge bases, aligning information across these diverse data sources remains a challenge in the literature.
• Previous work has partially addressed this issue by enriching knowledge graph entities based on "hard" co-occurrence of words present in the entities of the knowledge graphs and external text, while we achieve "soft" augmentation by proposing a knowledge graph enrichment and embedding framework named Edge.
• Given an original knowledge graph, we first generate a rich but noisy augmented graph using external texts in semantic and structural level.