Correcting Redundant Japanese Sentences Using Patterns and Machine Learning for the Development of Writing Support Systems

In this study, we propose a method to automatically correct redundant sentences using patterns and machine learning and propose methods that combine pattern-based and machine-learning methods. We conducted experiments to correct redundant sentences containing “kanou” (possible or possibility), “toiu” (“that is” or called), and “surukoto” (to do). The results demonstrate that the proposed method can correct redundant sentences at an accuracy of 0.6 and estimate corrected expressions against redundant parts at an accuracy of 0.7; furthermore, we created a method to support a user’s writing. In this method, a system displays redundant parts and provides candidate expressions.