EmbDI is a table embeddings algorithm that solves data integration problems by converting tabular data into graphs, then applying word2vec to the graph to obtain embeddings.
If the parameter for saving walks is set to true, the walks should be compressed after creating them, and uncompressed when it's time to train the embeddings.
If the parameter for saving walks is set to true, the walks should be compressed after creating them, and uncompressed when it's time to train the embeddings.