quangngoc Dimensionality of the one-hot vector will increase as the size of the corpus increases. The vector is mostly populated with zeros with only one useful data. Due to the dimensionality, an exponentially large memory will be used. For example, for a document of 50,000 vocabulary, we need 2,500,000,000 units of memory (50,000 * 50,000). It is hard to extract meaning from the one-hot vectors. The output contains mostly zeros and a single one, so the vector can not create relationships between the different words.