Fast2Vec, a modified model of FastText that enhances semantic analysis in topic evolution

Fast2Vec presents a robust and generalizable word embedding framework for semantic-based topic modeling. By combining the contextual sensitivity of Word2Vec with the subword flexibility of FastText, Fast2Vec effectively addresses prior limitations in handling OOV terms and semantic variation and demonstrates strong potential for boarder applications in natural language processing tasks.