Finding relevant features for Korean comparative sentence extraction

In this paper, we study how to extract comparative sentences from Korean text documents. We decompose our task into three steps: 1) collecting comparative keywords; 2) extracting comparative-sentence candidates by keyword searching; 3) eliminating non-comparative sentences from these candidates using machine learning techniques. We perform various experiments to find relevant features. As a result, our experiments show significant performance, an F1-score of 90.23%.