Development of an Extractive Title Generation System Using Titles of Papers of Top Conferences for Intermediate English Students

Kento Kaku, M. Kikuchi, Tadachika Ozono, T. Shintani
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Abstract

The formulation of good academic paper titles in English is challenging for intermediate English authors (particularly students). This is because such authors are not aware of the type of titles that are generally in use. We aim to realize a support system for formulating more effective English titles for intermediate English and beginner authors. This study develops an extractive title generation system that formulates titles from keywords extracted from an abstract. Moreover, we realize a title evaluation model that can evaluate the appropriateness of paper titles. We train the model with titles of top-conference papers by using BERT. This paper describes the training data, implementation, and experimental results. The results show that our evaluation model can identify top-conference titles more effectively than intermediate English and beginner students.
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基于顶级会议论文标题的中级英语学生抽取题目生成系统的开发
对于英语水平中等的作者(尤其是学生)来说,用英文写出好的学术论文标题是一项挑战。这是因为这些作者不知道通常使用的标题类型。我们的目标是实现一个支持系统,为中级英语和初级英语作者制定更有效的英语标题。本研究开发了一个提取标题生成系统,该系统从摘要中提取的关键词中制定标题。此外,我们还实现了一个可以对论文标题的适当性进行评价的标题评价模型。我们使用BERT来训练具有顶级会议论文标题的模型。本文描述了训练数据、实现和实验结果。结果表明,我们的评价模型比中级英语学习者和初级英语学习者更能有效地识别顶级会议标题。
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