Python NLP Spacy : improve bi-gram extraction from a dataframe, and with named entities?
I am using Python and spaCy as my NLP library, working on a big dataframe that contains feedback about different cars, which looks like this:
n-gram
n-grams in python, four, five, six grams?
I’m looking for a way to split a text into n-grams.
Normally I would do something like:
Computing N Grams using Python
I needed to compute the Unigrams, BiGrams and Trigrams for a text file containing text like:
Simple implementation of N-Gram, tf-idf and Cosine similarity in Python
I need to compare documents stored in a DB and come up with a similarity score between 0 and 1.