I am working on a project to extract a keyword from short texts (3-4 sentences). Using the spaCy library I extract noun phrases and NER and use them as keywords. However, I would like to sort them based on their importance wrt the original text.
I tried standard informational retrieval approaches, like tfidf, and even a couple of graph-based algorithms but having such short text the results weren't so great.
I was thinking that maybe using a NN with an attention mechanism could help me rank those keywords. Is there any way to use the pre-trained models that come with spaCy to do some kind of ranking?
How about something like maximal marginal relevance? http://www.cs.cmu.edu/~jgc/publication/The_Use_MMR_Diversity_Based_LTMIR_1998.pdf