Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks

To ensure readability, text is often written and presented with due formatting. These text formatting devices help the writer to effectively convey the narrative. At the same time, these help the readers pick up the structure of the discourse and comprehend the conveyed informa...

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Main Authors: Sachan, Mrinmaya, Dubey, Avinava, Hovy, Eduard H., Mitchell, Tom M., Roth, Dan, Xing, Eric P.
Format: Article
Language:English
Published: The MIT Press 2020-01-01
Series:Computational Linguistics
Online Access:https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00360
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spelling doaj-dc8f38f4640e4e158191ebcbb5855a152020-11-25T03:31:09ZengThe MIT PressComputational Linguistics0891-20171530-93122020-01-0145462766510.1162/coli_a_00360Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from TextbooksSachan, MrinmayaDubey, AvinavaHovy, Eduard H.Mitchell, Tom M.Roth, DanXing, Eric P. To ensure readability, text is often written and presented with due formatting. These text formatting devices help the writer to effectively convey the narrative. At the same time, these help the readers pick up the structure of the discourse and comprehend the conveyed information. There have been a number of linguistic theories on discourse structure of text. However, these theories only consider unformatted text. Multimedia text contains rich formatting features that can be leveraged for various NLP tasks. In this article, we study some of these discourse features in multimedia text and what communicative function they fulfill in the context. As a case study, we use these features to harvest structured subject knowledge of geometry from textbooks. We conclude that the discourse and text layout features provide information that is complementary to lexical semantic information. Finally, we show that the harvested structured knowledge can be used to improve an existing solver for geometry problems, making it more accurate as well as more explainable. https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00360
collection DOAJ
language English
format Article
sources DOAJ
author Sachan, Mrinmaya
Dubey, Avinava
Hovy, Eduard H.
Mitchell, Tom M.
Roth, Dan
Xing, Eric P.
spellingShingle Sachan, Mrinmaya
Dubey, Avinava
Hovy, Eduard H.
Mitchell, Tom M.
Roth, Dan
Xing, Eric P.
Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
Computational Linguistics
author_facet Sachan, Mrinmaya
Dubey, Avinava
Hovy, Eduard H.
Mitchell, Tom M.
Roth, Dan
Xing, Eric P.
author_sort Sachan, Mrinmaya
title Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
title_short Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
title_full Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
title_fullStr Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
title_full_unstemmed Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks
title_sort discourse in multimedia: a case study in extracting geometry knowledge from textbooks
publisher The MIT Press
series Computational Linguistics
issn 0891-2017
1530-9312
publishDate 2020-01-01
description To ensure readability, text is often written and presented with due formatting. These text formatting devices help the writer to effectively convey the narrative. At the same time, these help the readers pick up the structure of the discourse and comprehend the conveyed information. There have been a number of linguistic theories on discourse structure of text. However, these theories only consider unformatted text. Multimedia text contains rich formatting features that can be leveraged for various NLP tasks. In this article, we study some of these discourse features in multimedia text and what communicative function they fulfill in the context. As a case study, we use these features to harvest structured subject knowledge of geometry from textbooks. We conclude that the discourse and text layout features provide information that is complementary to lexical semantic information. Finally, we show that the harvested structured knowledge can be used to improve an existing solver for geometry problems, making it more accurate as well as more explainable.
url https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00360
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