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Scientific document processing: challenges for modern learning methods

Neural network models enjoy success on language tasks related to Web documents, including news and Wikipedia articles. However, the characteristics of scientific publications pose specific challenges that have yet to be satisfactorily addressed: the discourse structure of scientific documents crucia...

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Detalles Bibliográficos
Autores principales: Ramesh Kashyap, Abhinav, Yang, Yajing, Kan, Min-Yen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036973/
https://www.ncbi.nlm.nih.gov/pubmed/37361127
http://dx.doi.org/10.1007/s00799-023-00352-7
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author Ramesh Kashyap, Abhinav
Yang, Yajing
Kan, Min-Yen
author_facet Ramesh Kashyap, Abhinav
Yang, Yajing
Kan, Min-Yen
author_sort Ramesh Kashyap, Abhinav
collection PubMed
description Neural network models enjoy success on language tasks related to Web documents, including news and Wikipedia articles. However, the characteristics of scientific publications pose specific challenges that have yet to be satisfactorily addressed: the discourse structure of scientific documents crucial in scholarly document processing (SDP) tasks, the interconnected nature of scientific documents, and their multimodal nature. We survey modern neural network learning methods that tackle these challenges: those that can model discourse structure and their interconnectivity and use their multimodal nature. We also highlight efforts to collect large-scale datasets and tools developed to enable effective deep learning deployment for SDP. We conclude with a discussion on upcoming trends and recommend future directions for pursuing neural natural language processing approaches for SDP.
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spelling pubmed-100369732023-03-24 Scientific document processing: challenges for modern learning methods Ramesh Kashyap, Abhinav Yang, Yajing Kan, Min-Yen Int J Digit Libr Article Neural network models enjoy success on language tasks related to Web documents, including news and Wikipedia articles. However, the characteristics of scientific publications pose specific challenges that have yet to be satisfactorily addressed: the discourse structure of scientific documents crucial in scholarly document processing (SDP) tasks, the interconnected nature of scientific documents, and their multimodal nature. We survey modern neural network learning methods that tackle these challenges: those that can model discourse structure and their interconnectivity and use their multimodal nature. We also highlight efforts to collect large-scale datasets and tools developed to enable effective deep learning deployment for SDP. We conclude with a discussion on upcoming trends and recommend future directions for pursuing neural natural language processing approaches for SDP. Springer Berlin Heidelberg 2023-03-24 /pmc/articles/PMC10036973/ /pubmed/37361127 http://dx.doi.org/10.1007/s00799-023-00352-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ramesh Kashyap, Abhinav
Yang, Yajing
Kan, Min-Yen
Scientific document processing: challenges for modern learning methods
title Scientific document processing: challenges for modern learning methods
title_full Scientific document processing: challenges for modern learning methods
title_fullStr Scientific document processing: challenges for modern learning methods
title_full_unstemmed Scientific document processing: challenges for modern learning methods
title_short Scientific document processing: challenges for modern learning methods
title_sort scientific document processing: challenges for modern learning methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036973/
https://www.ncbi.nlm.nih.gov/pubmed/37361127
http://dx.doi.org/10.1007/s00799-023-00352-7
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