NLP pipeline for stopword removal and stemming, resulting text is processed into unigrams) but instead of one-hot vectors, GloVe vector embeddings are used.
the 300dimensional GloVe vectors trained on the large Common Crawl corpus of 840 billion tokens with a vocabulary of 2.2 million words.