OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques
Ontology alignment (OA) has evolved through several methodological paradigms, ranging from lexical and structural aligners to knowledge graph embedding (KGE) models and, more recently, Large Language Model (LLM)-based approaches. Although modern OA frameworks provide unified ecosystems for deploying these heterogeneous aligners, mechanisms for systematically reconciling their complementary and sometimes conflicting predictions remain relatively underexplored. We present OntoAligner-Ensemble, a modular and aligner-agnostic framework that combines candidate correspondences through a configurable
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- PossiblePossibly related (embedding) · 46%Ontology Reasoning AI: OWL Logic Meets Large Language Models - AI CERTs →
- FuzzySimilar title/name (fuzzy) · 87%NirDiamant/RAG_Techniques →
“Fuzzy title match (0.94): “OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneo” ≈ “NirDiamant/RAG_Techniques””
- LinkedLinked via arxiv author · 85%Hamed Babaei Giglou →
“OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques”
- LinkedLinked via arxiv author · 85%Sören Auer →
“OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques”
- LinkedLinked via arxiv author · 85%Peio Popov →
“OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques”
- LinkedLinked via arxiv author · 85%Mahsa Sanaei →
“OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques”
- LinkedLinked via arxiv author · 85%Jennifer D'Souza →
“OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques”
- FuzzySimilar title/name (fuzzy) · 84%satellite-image-deep-learning/techniques →
“Fuzzy title match (0.92): “OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneo” ≈ “satellite-image-deep-learning/techniques””