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:
nlp
Similarity between multiple vectors having same length
Objective : Compute a similarity between two users on the basis of their skills
Counting word frequency in a sentence
I have two columns – one with sentences and the other with single words.
How to compute the similarity between two text documents?
I am looking at working on an NLP project, in any programming language (though Python will be my preference).
Calculate cosine similarity given 2 sentence strings
From Python: tf-idf-cosine: to find document similarity , it is possible to calculate document similarity using tf-idf cosine. Without importing external libraries, are that any ways to calculate cosine similarity between 2 strings?
Creating a new corpus with NLTK
I reckoned that often the answer to my title is to go and read the documentations, but I ran through the NLTK book but it doesn’t give the answer. I’m kind of new to Python.
Stopword removal with NLTK
I am trying to process a user entered text by removing stopwords using nltk toolkit, but with stopword-removal the words like ‘and’, ‘or’, ‘not’ gets removed. I want these words to be present after stopword removal process as they are operators which are required for later processing text as query. I don’t know which are the words which can be operators in text query, and I also want to remove unnecessary words from my text.
How to determine the language of a piece of text?
I want to get this:
Ordinal numbers replacement
I am currently looking for the way to replace words like first, second, third,…with appropriate ordinal number representation (1st, 2nd, 3rd).
I have been googling for the last week and I didn’t find any useful standard tool or any function from NLTK.