Supporting content evaluation of student summaries by idea unit embedding

Marcello Gecchele, Hiroaki Yamada, Takenobu Tokunaga, Yasuyo Sawaki

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

Abstract

This paper discusses the computer-assisted content evaluation of summaries. We propose a method to make a correspondence between the segments of the source text and its summary. As a unit of the segment, we adopt "Idea Unit (IU)" which is proposed in Applied Linguistics. Introducing IUs enables us to make a correspondence even for the sentences that contain multiple ideas. The IU correspondence is made based on the similarity between vector representations of IU. An evaluation experiment with two source texts and 20 summaries showed that the proposed method is more robust against rephrased expressions than the conventional ROUGEbased baselines. Also, the proposed method outperformed the baselines in recall. We implemented the proposed method in a GUI tool "Segment Matcher" that aids teachers to establish a link between corresponding IUs across the summary and source text.

Original languageEnglish
Title of host publicationACL 2019 - Innovative Use of NLP for Building Educational Applications, BEA 2019 - Proceedings of the 14th Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages343-348
Number of pages6
ISBN (Electronic)9781950737345
Publication statusPublished - 2019
Event14th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2019, collocated with ACL 2019 - Florence, Italy
Duration: 2019 Aug 2 → …

Publication series

NameACL 2019 - Innovative Use of NLP for Building Educational Applications, BEA 2019 - Proceedings of the 14th Workshop

Conference

Conference14th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2019, collocated with ACL 2019
Country/TerritoryItaly
CityFlorence
Period19/8/2 → …

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Software

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