用协作学习提升作文评分准确率，达85.5%
Hey AI Can You Grade My Essay?: Automatic Essay Grading
- 分工协作：一个网络管语法结构，另一个管内容思想
- 模型综合两者输出，评分准确率达85.50%
- 适合教育评测与自动评分系统开发者参考
自动作文评分（AEG）因在作文、简答题等教育场景中的应用而受到自然语言处理领域的关注。现有方法多采用单一网络完成评分，可能因无法全面捕捉人类写作特征而效果受限。本文提出一种新模型，结合协同学习与迁移学习机制：一个网络负责分析句子的语法和结构特征，另一个网络评估文章整体思想内容，再将二者学习成果迁移至最终评分网络。实验对比显示，所提模型在标准数据集上达到85.50%的最高准确率，优于当前主流方法。
原文摘要 · Abstract (English)
Automatic essay grading (AEG) has attracted the the attention of the NLP community because of its applications to several educational applications, such as scoring essays, short answers, etc. AEG systems can save significant time and money when grading essays. In the existing works, the essays are graded where a single network is responsible for the whole process, which may be ineffective because a single network may not be able to learn all the features of a human-written essay. In this work, we have introduced a new model that outperforms the state-of-the-art models in the field of AEG. We have used the concept of collaborative and transfer learning, where one network will be responsible for checking the grammatical and structural features of the sentences of an essay while another network is responsible for scoring the overall idea present in the essay. These learnings are transferred to another network to score the essay. We also compared the performances of the different models mentioned in our work, and our proposed model has shown the highest accuracy of 85.50%.
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