We propose an alternative approach that is based on matrix norms and which proved to be more noise-robust by focusing primarily on high word similarities.
the most popular method to come up with word vectors is Word2Vec, which is based on a 3 layer neural network architecture in which the word vectors are obtained as the weights of the hidden layer.