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Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links

Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to v...

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Autores principales: Dascalu, Maria-Dorinela, Ruseti, Stefan, Dascalu, Mihai, McNamara, Danielle S., Trausan-Matu, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334671/
http://dx.doi.org/10.1007/978-3-030-52240-7_15
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author Dascalu, Maria-Dorinela
Ruseti, Stefan
Dascalu, Mihai
McNamara, Danielle S.
Trausan-Matu, Stefan
author_facet Dascalu, Maria-Dorinela
Ruseti, Stefan
Dascalu, Mihai
McNamara, Danielle S.
Trausan-Matu, Stefan
author_sort Dascalu, Maria-Dorinela
collection PubMed
description Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to visualize text cohesion both within (intra) and between (inter) texts. This tool, Multi-document Cohesion Network Analysis (MD-CNA), expands the structure of a CNA graph with lexical overlap links of multiple types, together with coreference links to highlight dependencies between text fragments of different granularities. We introduce two visualizations of the CNA graph that support the visual exploration of intratextual and intertextual links. First, a hierarchical view displays a tree-structure of discourse as a visual illustration of CNA links within a document. Second, a grid view available at paragraph or sentence levels displays links both within and between documents, thus ensuring ease of visualization for links spanning across multiple documents. Two use cases are provided to evaluate key functionalities and insights for each type of visualization.
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spelling pubmed-73346712020-07-06 Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links Dascalu, Maria-Dorinela Ruseti, Stefan Dascalu, Mihai McNamara, Danielle S. Trausan-Matu, Stefan Artificial Intelligence in Education Article Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to visualize text cohesion both within (intra) and between (inter) texts. This tool, Multi-document Cohesion Network Analysis (MD-CNA), expands the structure of a CNA graph with lexical overlap links of multiple types, together with coreference links to highlight dependencies between text fragments of different granularities. We introduce two visualizations of the CNA graph that support the visual exploration of intratextual and intertextual links. First, a hierarchical view displays a tree-structure of discourse as a visual illustration of CNA links within a document. Second, a grid view available at paragraph or sentence levels displays links both within and between documents, thus ensuring ease of visualization for links spanning across multiple documents. Two use cases are provided to evaluate key functionalities and insights for each type of visualization. 2020-06-10 /pmc/articles/PMC7334671/ http://dx.doi.org/10.1007/978-3-030-52240-7_15 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Dascalu, Maria-Dorinela
Ruseti, Stefan
Dascalu, Mihai
McNamara, Danielle S.
Trausan-Matu, Stefan
Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links
title Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links
title_full Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links
title_fullStr Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links
title_full_unstemmed Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links
title_short Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links
title_sort multi-document cohesion network analysis: visualizing intratextual and intertextual links
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334671/
http://dx.doi.org/10.1007/978-3-030-52240-7_15
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