Graph Neural Network Approach to Semantic Type Detection in Tables

arXiv:2405.00123v1 Announce Type: new
Abstract: This study addresses the challenge of detecting semantic column types in relational tables, a key task in many real-world applications. While language models like BERT have improved prediction accuracy, their token input constraints limit the simultaneous processing of intra-table and inter-table information. We propose a novel approach using Graph Neural Networks (GNNs) to model intra-table dependencies, allowing language models to focus on inter-table information. Our proposed method not only outperforms existing state-of-the-art algorithms but also …

arxiv cs.cl cs.lg detection graph graph neural network network neural network semantic tables type