New Paper: Learning Robust Food Ontology Alignment
Our paper from the IEEE Conference on Big Data 2022 (Osaka, Japan) has now been published online. "Learning Robust Food Ontology Alignment" is a work by our team at the Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia.
In the paper, we show how ontology alignment can be performed using neural networks. Each semantic resource is represented as a combination of graph based representations (#RDF2vec) and text representations (#BERT), in order to capture its semantic and structural features.
With this, we get a methodology for ontology alignment that is both robust and ontology-agnostic. It can be applied to any ontology, regardless of the domain.
Congrats to the team: Viktorija Mijalcheva, Ana Davcheva, Sasho Gramatikov, Milos Jovanovik, Dimitar Trajanov and Riste Stojanov.
Paper: https://ieeexplore.ieee.org/document/10020417