We are fully aware of the marked influence of the introduction of Word2Vec method of word embedding on the Natural Language Processing domain. It was a huge leap forward from the hitherto constricting method of word embeddings namely, Term Frequency (TF) and Inverse Document Frequency (IDF). Neither of these methods were anywhere close to preserving the semantics of the words in their representations. With the introduction of Word2Vec and the possibility of semantic embedding in the vectors, ...