  One key task of fine-grained sentiment analysis on reviews is to extract
aspects or features that users have expressed opinions on. This paper focuses
on supervised aspect extraction using a modified CNN called controlled CNN
(Ctrl). The modified CNN has two types of control modules. Through asynchronous
parameter updating, it prevents over-fitting and boosts CNN's performance
significantly. This model achieves state-of-the-art results on standard aspect
extraction datasets. To the best of our knowledge, this is the first paper to
apply control modules to aspect extraction.
