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Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion

In recent years, there has been increased interest in topic-focused multi-document summarization. In this task, automatic summaries are produced in response to a specific information request, or topic, stated by the user. The system we have designed to accomplish this task comprises four main compon...

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Detalles Bibliográficos
Autores principales: Vanderwende, Lucy, Suzuki, Hisami, Brockett, Chris, Nenkova, Ani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115785/
https://www.ncbi.nlm.nih.gov/pubmed/32287938
http://dx.doi.org/10.1016/j.ipm.2007.01.023
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author Vanderwende, Lucy
Suzuki, Hisami
Brockett, Chris
Nenkova, Ani
author_facet Vanderwende, Lucy
Suzuki, Hisami
Brockett, Chris
Nenkova, Ani
author_sort Vanderwende, Lucy
collection PubMed
description In recent years, there has been increased interest in topic-focused multi-document summarization. In this task, automatic summaries are produced in response to a specific information request, or topic, stated by the user. The system we have designed to accomplish this task comprises four main components: a generic extractive summarization system, a topic-focusing component, sentence simplification, and lexical expansion of topic words. This paper details each of these components, together with experiments designed to quantify their individual contributions. We include an analysis of our results on two large datasets commonly used to evaluate task-focused summarization, the DUC2005 and DUC2006 datasets, using automatic metrics. Additionally, we include an analysis of our results on the DUC2006 task according to human evaluation metrics. In the human evaluation of system summaries compared to human summaries, i.e., the Pyramid method, our system ranked first out of 22 systems in terms of overall mean Pyramid score; and in the human evaluation of summary responsiveness to the topic, our system ranked third out of 35 systems.
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spelling pubmed-71157852020-04-02 Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion Vanderwende, Lucy Suzuki, Hisami Brockett, Chris Nenkova, Ani Inf Process Manag Article In recent years, there has been increased interest in topic-focused multi-document summarization. In this task, automatic summaries are produced in response to a specific information request, or topic, stated by the user. The system we have designed to accomplish this task comprises four main components: a generic extractive summarization system, a topic-focusing component, sentence simplification, and lexical expansion of topic words. This paper details each of these components, together with experiments designed to quantify their individual contributions. We include an analysis of our results on two large datasets commonly used to evaluate task-focused summarization, the DUC2005 and DUC2006 datasets, using automatic metrics. Additionally, we include an analysis of our results on the DUC2006 task according to human evaluation metrics. In the human evaluation of system summaries compared to human summaries, i.e., the Pyramid method, our system ranked first out of 22 systems in terms of overall mean Pyramid score; and in the human evaluation of summary responsiveness to the topic, our system ranked third out of 35 systems. Elsevier Ltd. 2007-11 2007-04-19 /pmc/articles/PMC7115785/ /pubmed/32287938 http://dx.doi.org/10.1016/j.ipm.2007.01.023 Text en Copyright © 2007 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Vanderwende, Lucy
Suzuki, Hisami
Brockett, Chris
Nenkova, Ani
Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
title Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
title_full Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
title_fullStr Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
title_full_unstemmed Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
title_short Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion
title_sort beyond sumbasic: task-focused summarization with sentence simplification and lexical expansion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115785/
https://www.ncbi.nlm.nih.gov/pubmed/32287938
http://dx.doi.org/10.1016/j.ipm.2007.01.023
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