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

• URL: http://arxiv.org/abs/2110.04204v1
• Date: Fri, 8 Oct 2021 15:41:27 GMT
• Title: Development of an Extractive Title Generation System Using Titles of Papers of Top Conferences for Intermediate English Students
• Authors: Kento Kaku, Masato Kikuchi, Tadachika Ozono, Toramatsu Shintani
• Abstract summary: This study develops an extractive title generation system that formulates titles from keywords extracted from an abstract. We also realize a title evaluation model that can evaluate the appropriateness of paper titles. The results show that our evaluation model can identify top-conference titles more effectively than intermediate English and beginner students.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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