University of Illinois system in HOO text correction shared task

In this paper, we describe the University of Illinois system that participated in Helping Our Own (HOO), a shared task in text correction. We target several common errors, such as articles, prepositions, word choice, and punctuation errors, and we describe the approaches taken to address each error type. Our system is based on a combination of classifiers, combined with adaptation techniques for article and preposition detection. We ranked first in all three evaluation metrics (Detection, Recognition and Correction) among six participating teams. We also present type-based scores on preposition and article error correction and demonstrate that our approach achieves best performance in each task.