The neural symbolic model proposed by Lemos et al. (2020) operates by taking a subset of a knowledge graph as input and utilizing two learned embedding layers to map entity types and relationships into a real-valued vector space, thereby capturing the underlying semantic features of those entities and relationships.

Authors

• Person: Not available Organization: arXiv
  Neuro-Symbolic AI: Explainability, Challenges, and Future Trends

Sources

• Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org arXiv via serper

Referenced by nodes (1)

• Knowledge Graph concept