Dec 30, 2021 · This study presents our research on the development of new methods for ontology matching that are accurate and interpretable at the same time.

For this purpose, we rely on a symbolic regression model (implemented via genetic programming) that has been specifically trained to find the mathematical ...

This study presents our research on the development of new methods for ontology matching that are accurate and interpretable at the same time.

We propose a method to automatically match large biomedical ontologies based on the concept of symbolic regression intended to facilitate the interpretability ...

This method has been compared with four well-known Symbolic Regression techniques with a large number of datasets. As a result, on average, the proposed method ...

Matching Large Biomedical Ontologies Using Symbolic Regression. https://doi ... Efficient large-scale biomedical ontology matching with anchor-based biomedical ...

Unlike the most recent developments based on deep learning, this study presents our research efforts on the development of novel methods for ontology matching ...

Efficient large-scale biomedical ontology matching with anchor-based biomedical ontology partitioning and compact geometric semantic genetic programming.

This paper proposes a novel ontology alignment system based on a contextual embedding model named BERT, aiming to utilize the text semantics implied by ...

This paper proposes an efficient BOM method to automatically match large-scale biomedical ontologies.