library(wordVectors)
prep_word2vec(origin="complaints_text.txt",
	destination="complaints_text_prep.txt",
	lowercase=TRUE,
	bundle_ngrams=1)


model <- train_word2vec(train_file="complaints_text_prep.txt",
	output_file="complaints_text.bin",
	vectors=150,
	threads=4,
	min_count=3,
	window=5,
	iter=5,
	negative_samples=10,
    force=TRUE)

x <- model["account", ]
closest_to(model, x)

x <- model["steak", ] - model["beef", ] + model["pork", ]
closest_to(model, x)