Thank “Goodness”! A Way to Measure Style in Student Essays

NLP-TEA@ACL Pub Date : 2018-07-01 DOI:10.18653/v1/W18-3705
Sandeep Albert Mathias, P. Bhattacharyya
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引用次数: 7

Abstract

Essays have two major components for scoring - content and style. In this paper, we describe a property of the essay, called goodness, and use it to predict the score given for the style of student essays. We compare our approach to solve this problem with baseline approaches, like language modeling and also a state-of-the-art deep learning system. We show that, despite being quite intuitive, our approach is very powerful in predicting the style of the essays.
谢谢“善良”!一种衡量学生作文风格的方法
文章有两个主要的评分组成部分——内容和风格。在本文中,我们描述了作文的一个属性,称为善良,并用它来预测学生作文风格的分数。我们将解决这个问题的方法与基线方法(如语言建模和最先进的深度学习系统)进行比较。我们表明,尽管我们的方法非常直观,但在预测文章风格方面非常强大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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