Huang et al. (2019) proposed a knowledge graph embedding-based question-answering system (KEQA) that translates questions and answers into single triplets, such as (Leonardo, act, Inception), and represents the head entity, relation, and tail entity as a vector matrix in an embedding space.

Authors

• Person: Not available Organization: Springer
  Knowledge Graphs: Opportunities and Challenges - Springer Nature

Sources

• Knowledge Graphs: Opportunities and Challenges - Springer Nature link.springer.com Springer via serper

Referenced by nodes (2)

• Knowledge Graph Question Answering concept
• triplets concept