Order Embeddings from Merged Ontologies using Sketching

TL;DR

This paper introduces a low-resource method using sketching techniques to create order embeddings from ontologies, effectively preserving hierarchical relations across domains.

Contribution

It presents a novel approach combining sketching with ontology merging to produce accurate order embeddings in both generic and specialized domains.

Findings

Effective merging of medical ontologies demonstrated

Accurate order embeddings for WordNet and medical ontologies

Sketching techniques enable low-resource embedding creation

Abstract

We give a simple, low resource method to produce order embeddings from ontologies. Such embeddings map words to vectors so that order relations on the words, such as hypernymy/hyponymy, are represented in a direct way. Our method uses sketching techniques, in particular countsketch, for dimensionality reduction. We also study methods to merge ontologies, in particular those in medical domains, so that order relations are preserved. We give computational results for medical ontologies and for wordnet, showing that our merging techniques are effective and our embedding yields an accurate representation in both generic and specialised domains.