In the realm of natural language processing, tag embeddings stand as a strong tool for capturing and representing the nuances of text. By transforming copyright or phrases into numerical vectors, tag embeddings enable machines to interpret the semantic meaning of text with unprecedented accuracy. This opens up a wide array of applications in fields