MATEC Web Conf.
Volume 232, 20182018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|Number of page(s)||4|
|Section||3D Images Reconstruction and Virtual System|
|Published online||19 November 2018|
RST-based Discourse Coherence Quality Analysis Model for Students’ English Essays
School of Information and Communication Engineering, Guilin University of Electronic Technology, Guilin, China
a Corresponding author: firstname.lastname@example.org
Against the problems which can’t be solved by the word-level based local coherence analysis model, we propose a new discourse coherence quality analysis model (abbreviated RST-DCQA) by analyzing the full hierarchical discourse structure of English essays. Under the framework of rhetorical structure theory (RST), firstly, we design an RST-style discourse relations parser to capture the deep hierarchical discourse structure of essays; secondly, we transform the discourse relation information into a discourse relation matrix; finally, we design an algorithm to analyze the discourse coherence quality of student’s English essays. The experimental results show that the average error of our model’s score and teacher’s score is only 2.63, and the Pearson correlation coefficient is 0.71. Compared with the other models, our RST-DCQA model has a higher accuracy and better practicality in the field of students’ essays assessment.
© The Authors, published by EDP Sciences, 2018
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