In the realm of natural language processing, tag embeddings stand as a powerful tool for capturing and representing the subtleties of text. By transforming copyright or phrases into numerical vectors, tag embeddings enable machines to interpret the semantic context of text with unprecedented accuracy. This opens up a vast array of opportunities in