Abstract
Word embedding is a technique for converting a word into a vector. These are known as word vectors. Despite the fact that word embedding offers multiple powerful approaches, these existing methods can yet be improved. Normalizing word vectors and establishing orthogonal transformation algorithms are two of the method developments. The advancement of this technology has also resulted in improved results in future studies such as word similarity and word translation assignments. With the presence of these method developments, it is possible that the produced methods will be further improved into better word embedding methods in the future
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