Feature Construction for Text Classification using Autoencoders <p>Autoencoders can be used to reduce dimensionallity in feature vectors - as far as I understand. In text classification a feature vector is normally constructed via a dictionary - which tends to be extremely large. I have no experience in using autoencoders, so my questions are:</p> <ol> <li>Could autoencoders be used to reduce dimensionallity in text classification? (Why? / Why not?)</li> <li>Has anyone already done this? A source would be nice, if so.</li> </ol>