Enhancing automatic Chinese essay scoring system from figures-of-speech

Abstract

Chinese automated essay scoring (CAES) is a very important tool for many educational researches. However, none of the methods for retrieving features in English essays is applicable to Chinese writings because Chinese grammar parsers cannot produce reliable and useful syntactic features. CAES systems must explore other distinct features in Chinese writing. This paper proposes a method for retrieving two Chinese figures-of-speech from essays and to predict the scores of essays based on the two skills used in the essays. A scoring model based on ID3 decision tree algorithm will validate and show that the proposed method increases the performance of CAES effectively.