Additionally, the simplicity entailed by the vector space abstraction makes it an engineering-friendly representation, also explaining its widespread adoption and use (Freitas, 2015).
the latent features (dense vectors) at the center of most of the best-performing models have limited their application to two main uses: (i) computing semantic similarity and relat-edness measures and (ii) performing vocabulary generalization as an input layer on Machine Learning (ML) models.