Relational Pattern Learning

Relational Pattern Learning refers to the process of learning and extracting implicit patterns between relationships from a knowledge graph. This task aims to discover potential structured associations by analyzing the relationships between entities, thereby enhancing the completeness and accuracy of the knowledge graph. These patterns help to strengthen knowledge representation, optimize inference capabilities, and play a significant role in areas such as recommendation systems, semantic search, and natural language processing.