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Have you considered using PLSA (Probabilistic latent semantic analysis)? Effectively, this method does very similiar thing as you aim to do - it chooses a set of words that represen a topic of a document.



Great suggestion. We've used LDA for topic modeling in the past. I'm a big fan of running word2vec and clustering.


> I'm a big fan of running word2vec and clustering.

Can you explain more about this?


Opentable gave a great presentation on this not too long ago, check it out http://www.slideshare.net/SudeepDasPhD/recsys-2015-making-me...




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