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I have a list of similar sentences, and I would like to automatically extract top-n important keywords [single word length] from a whole set of those sentences by using python. These sentences are already in normalized form as they do not contain stop words.

Those top-n important keywords should be a representation of those similar sentences.

Which technique should I follow such as summarization technique, keyword extraction technique, or topic modeling technique?

I know TF-IDF, RAKE etc but I how can I utilize them to achieve my goal? Can you please suggest some code snippet which can work well to achieve that goal?

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