A Machine Learning Approach to Answering Questions for Reading Comprehension Tests

Abstract

In this paper, we report results on answering questions for the reading comprehension task, using a machine learning approach. We evaluated our approach on the Remédia data set, a common data set used in several recent papers on the reading comprehension task. Our learning approach achieves accuracy competitive to previous approaches that rely on handcrafted, deterministic rules and algorithms. To the best of our knowledge, this is the first work that reports that the use of a machine learning approach achieves competitive results on answering questions for reading comprehension tests.