A causal discovery-based adaptive fusion algorithm for multi-source heterogeneous knowledge graphs

Multi-source heterogeneous knowledge graph fusion faces significant challenges due to schema heterogeneity, entity conflicts, and relationship inconsistencies across different knowledge sources. This paper proposes CausalFusion, a novel adaptive fusion algorithm that leverages causal discovery principles to guide the knowledge graph integration process. The algorithm incorporates a constraint-based causal discovery component specifically designed for relational data, an adaptive weight learning...