Ontology Matching Through Absolute Orientation of Embedding Spaces
Ontology matching is a core task when creating interoperable and linked open datasets. In this paper, we explore a novel structure-based mapping approach which is based on knowledge graph embeddings: The ontologies to be matched are embedded, and an approach known as absolute orientation is used to align the two embedding spaces. Next to the approach, the paper presents a first, preliminary evaluation using synthetic and real-world datasets. We find in experiments with synthetic data, that the approach works very well on similarly structured graphs; it handles alignment noise better than size and structural differences in the ontologies.
Code (1)
Tasks
Knowledge Graph EmbeddingsOntology MatchingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
A Self-matching Training Method with Annotation Embedding Models for Ontology Subsumption Prediction
Recently, ontology embeddings representing entities in a low-dimensional space have been proposed for ontology completion. However, the ontology embeddings for concept subsumption prediction do not address the difficulti…
Ontology EmbeddingExploring Wasserstein Distance across Concept Embeddings for Ontology Matching
Measuring the distance between ontological elements is fundamental for ontology matching. String-based distance metrics are notorious for shallow syntactic matching. In this exploratory study, we investigate Wasserstein …
Ontology MatchingWord EmbeddingsBreaking-down the Ontology Alignment Task with a Lexical Index and Neural Embeddings
Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In the paper we present an approach that combines a lexical index, a neural embedding model and locality modules to effective…
Ontology MatchingDividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules
Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In this paper we present an approach that combines a neural embedding model and logic-based modules to accurately divide an i…
Ontology MatchingComplex Ontology Matching with Large Language Model Embeddings
Ontology, and more broadly, Knowledge Graph Matching is a challenging task in which expressiveness has not been fully addressed. Despite the increasing use of embeddings and language models for this task, approaches for …
Graph MatchingLanguage ModelingLanguage ModellingLarge Language Model+5