I read about Recursive Neural Networks that they can convert Documents to distributed word representation.
In the context of new article recommendation, I am thinking to use this model to convert all news articles to vectors and then recommend to a particular user, news articles similar to ones he browsed.
In vector space this will boil down to finding 'similar' vectors to a given vector(user's news read).
How likely is that this model will work well in practice? Any comments and/or suggestions?