I am looking at querying a text database based on keywords and getting the relevant chunks. I want to know what is the difference between python's kwx package and sklearn's tfidfvectoriser in implementing this. Even though kwx extracts keywords and topics, looks like I can't perform a keyword based search using it, For which I anyway have to use sklearn's tfidf vectorizer. Can you please help me understand the difference and implement an elegant solution? TIA :)