A title generation method with Transformer for journal articles

Matsumoto Riku, Kimura Masaomi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

While many methods of summarization have been proposed, there have been few methods to generate a title, especially for journal articles. However, the differences between summarization and creating a title are length and clause form. We propose a title generation model for a journal article based on Transformer, which refers to a wide range of the article. We propose to narrow down the abstract sentences to only important sentences before title generation so that the author's claim can be easily reflected in the title. We applied our method to journal articles published on arXiv.org and found that our model generated a title including words in the original title.

Original languageEnglish
Title of host publicationProceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1115-1120
Number of pages6
ISBN (Electronic)9786165904773
DOIs
Publication statusPublished - 2022
Event2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022 - Chiang Mai, Thailand
Duration: 2022 Nov 72022 Nov 10

Publication series

NameProceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022

Conference

Conference2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
Country/TerritoryThailand
CityChiang Mai
Period22/11/722/11/10

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

Cite this