Semantic Type Detection

Semantic type detection is an important task in table representation learning, as it involves labeling table columns with standardized semantic types. This can help with understanding the contents of a table and can be used for various applications such as data discovery, data validation, and data integration. By accurately detecting the semantic types of columns, machine learning models can better understand the relationships between columns and improve their performance on tasks like table comprehension and data discovery. Additionally, semantic type detection can help with data integration, as it can help map columns from different sources that may have different naming conventions or formats.

X::Table Representation Learning