#entity-classification News & Analysis

Rel-MOSS: Towards Imbalanced Relational Deep Learning on Relational Databases

Researchers introduce Rel-MOSS, a novel graph neural network approach designed to address class imbalance problems in relational database entity classification. The method uses relation-centric gating and minority oversampling techniques to prevent underrepresentation of minority classes, achieving 2-4% performance improvements over existing relational deep learning methods.