Recovering Dropped Pronouns From Chinese Text Messages

Pronouns are frequently dropped in Chinese sentences, especially in informal data such as text messages. In this work we propose a solution to recover dropped pronouns in SMS data. We manually annotate dropped pronouns in 684 SMS files and apply machine learning algorithms to recover them, leveraging lexical, contextual and syntactic information as features. We believe this is the first work on recovering dropped pronouns in Chinese text messages.