Automatic Extractive Single Document Summarization: A Systematic Mapping
Automatic Extractive Single Document Summarization (AESDS) is a research area that aims to create a condensed version of a document with the most relevant information; it acquires more importance daily due to the need of users to obtain information on documents published on the Internet quickly. In...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/14362
- Acceso en línea:
- https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15232
https://repositorio.uptc.edu.co/handle/001/14362
- Palabra clave:
- Automatic text summarization
Extractive
Systematic mapping
Generación automática de resúmenes
Extractivo
Mapeo Sistemático
- Rights
- License
- http://creativecommons.org/licenses/by/4.0
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dc.title.en-US.fl_str_mv |
Automatic Extractive Single Document Summarization: A Systematic Mapping |
dc.title.es-ES.fl_str_mv |
Generación automática de resúmenes extractivos para un solo documento: un mapeo sistemático |
title |
Automatic Extractive Single Document Summarization: A Systematic Mapping |
spellingShingle |
Automatic Extractive Single Document Summarization: A Systematic Mapping Automatic text summarization Extractive Systematic mapping Generación automática de resúmenes Extractivo Mapeo Sistemático |
title_short |
Automatic Extractive Single Document Summarization: A Systematic Mapping |
title_full |
Automatic Extractive Single Document Summarization: A Systematic Mapping |
title_fullStr |
Automatic Extractive Single Document Summarization: A Systematic Mapping |
title_full_unstemmed |
Automatic Extractive Single Document Summarization: A Systematic Mapping |
title_sort |
Automatic Extractive Single Document Summarization: A Systematic Mapping |
dc.subject.en-US.fl_str_mv |
Automatic text summarization Extractive Systematic mapping |
topic |
Automatic text summarization Extractive Systematic mapping Generación automática de resúmenes Extractivo Mapeo Sistemático |
dc.subject.es-ES.fl_str_mv |
Generación automática de resúmenes Extractivo Mapeo Sistemático |
description |
Automatic Extractive Single Document Summarization (AESDS) is a research area that aims to create a condensed version of a document with the most relevant information; it acquires more importance daily due to the need of users to obtain information on documents published on the Internet quickly. In automatic document summarization, each element must be evaluated and ranked to generate a summary. As such, there are three approaches considering the number of objectives they evaluate: single-objective, multi-objective, and many-objective. This systematic mapping aims to provide knowledge about the methods and techniques used in extractive techniques for AESDS, analyzing the number of objectives and characteristics evaluated, which can be helpful for future research. This mapping was carried out using a generic process for the realization of systematic reviews where a search string was built considering some research questions. A filter was then used with inclusion and exclusion criteria for selecting primary studies with which it will carry out the analysis. Additionally, these studies are sorted according to the relevance of their content. This process is summarized in three main steps: planning, execution, and result analysis. At the end of the mapping, the following observations were identified: (i) There is a preference for the use of machine learning methods and the use of clustering techniques, (ii) the importance of using both types of characteristics (statistics and semantics), and (iii) the need to explore the many-objective approach. |
publishDate |
2023 |
dc.date.accessioned.none.fl_str_mv |
2024-07-05T19:12:09Z |
dc.date.available.none.fl_str_mv |
2024-07-05T19:12:09Z |
dc.date.none.fl_str_mv |
2023-02-28 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a169 |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15232 10.19053/01211129.v32.n63.2023.15232 |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.uptc.edu.co/handle/001/14362 |
url |
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15232 https://repositorio.uptc.edu.co/handle/001/14362 |
identifier_str_mv |
10.19053/01211129.v32.n63.2023.15232 |
dc.language.none.fl_str_mv |
eng |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15232/12707 https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15232/13184 |
dc.rights.en-US.fl_str_mv |
http://creativecommons.org/licenses/by/4.0 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_abf86 |
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http://creativecommons.org/licenses/by/4.0 http://purl.org/coar/access_right/c_abf86 http://purl.org/coar/access_right/c_abf2 |
dc.format.none.fl_str_mv |
application/pdf text/xml |
dc.publisher.en-US.fl_str_mv |
Universidad Pedagógica y Tecnológica de Colombia |
dc.source.en-US.fl_str_mv |
Revista Facultad de Ingeniería; Vol. 32 No. 63 (2023): January-March 2023 (Continuous Publication); e15232 |
dc.source.es-ES.fl_str_mv |
Revista Facultad de Ingeniería; Vol. 32 Núm. 63 (2023): Enero-Marzo 2023 (Publicación Continua); e15232 |
dc.source.none.fl_str_mv |
2357-5328 0121-1129 |
institution |
Universidad Pedagógica y Tecnológica de Colombia |
repository.name.fl_str_mv |
Repositorio Institucional UPTC |
repository.mail.fl_str_mv |
repositorio.uptc@uptc.edu.co |
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1839633801276293120 |
spelling |
2023-02-282024-07-05T19:12:09Z2024-07-05T19:12:09Zhttps://revistas.uptc.edu.co/index.php/ingenieria/article/view/1523210.19053/01211129.v32.n63.2023.15232https://repositorio.uptc.edu.co/handle/001/14362Automatic Extractive Single Document Summarization (AESDS) is a research area that aims to create a condensed version of a document with the most relevant information; it acquires more importance daily due to the need of users to obtain information on documents published on the Internet quickly. In automatic document summarization, each element must be evaluated and ranked to generate a summary. As such, there are three approaches considering the number of objectives they evaluate: single-objective, multi-objective, and many-objective. This systematic mapping aims to provide knowledge about the methods and techniques used in extractive techniques for AESDS, analyzing the number of objectives and characteristics evaluated, which can be helpful for future research. This mapping was carried out using a generic process for the realization of systematic reviews where a search string was built considering some research questions. A filter was then used with inclusion and exclusion criteria for selecting primary studies with which it will carry out the analysis. Additionally, these studies are sorted according to the relevance of their content. This process is summarized in three main steps: planning, execution, and result analysis. At the end of the mapping, the following observations were identified: (i) There is a preference for the use of machine learning methods and the use of clustering techniques, (ii) the importance of using both types of characteristics (statistics and semantics), and (iii) the need to explore the many-objective approach.La Generación Automática de Resúmenes Extractivos para un Solo Documento (GAReUD) es un área de investigación que tiene como objetivo crear una versión corta de un documento con la información más relevante y adquiere mayor importancia a diario debido a la necesidad de los usuarios de obtener rápidamente información de documentos publicados en internet. En el área de generación automática de resúmenes cada elemento debe ser evaluado y luego rankeado para conformar un resumen, de acuerdo con esto, existen tres diferentes enfoques teniendo en cuenta la cantidad de objetivos que se evalúan, así: mono objetivo, multi objetivo y de muchos objetivos. El propósito de este mapeo sistemático es brindar conocimiento sobre los métodos y técnicas utilizadas en métodos extractivos de GAReUD, analizando la cantidad de objetivos y características evaluadas, que pueden ser útiles para futuras investigaciones. Este mapeo se realizó utilizando un proceso genérico para la realización de revisiones sistemáticas donde se construye una cadena de búsqueda considerando unas preguntas de investigación, luego se utiliza un filtro con unos criterios de inclusión y exclusión para la selección de los estudios primarios con los que se realizará el análisis, adicionalmente, estos estudios se ordenan de acuerdo con la relevancia de su contenido; este proceso se resume en tres pasos principales: Planificación, Ejecución y Análisis de resultados. Al final del mapeo se identificaron las siguientes observaciones: (i) existe una preferencia por la utilización de métodos basados en aprendizaje automático de máquina y también por el uso de técnicas de agrupamiento, (ii) la importancia de usar como objetivos ambos tipos de características (estadísticas y semánticas) y (iii) la necesidad de explorar el enfoque de muchos objetivos.application/pdftext/xmlengengUniversidad Pedagógica y Tecnológica de Colombiahttps://revistas.uptc.edu.co/index.php/ingenieria/article/view/15232/12707https://revistas.uptc.edu.co/index.php/ingenieria/article/view/15232/13184Copyright (c) 2023 Juan-David Yip-Herrera, Martha-Eliana Mendoza-Becerra, Francisco-Javier Rodríguezhttp://creativecommons.org/licenses/by/4.0http://purl.org/coar/access_right/c_abf86http://purl.org/coar/access_right/c_abf2Revista Facultad de Ingeniería; Vol. 32 No. 63 (2023): January-March 2023 (Continuous Publication); e15232Revista Facultad de Ingeniería; Vol. 32 Núm. 63 (2023): Enero-Marzo 2023 (Publicación Continua); e152322357-53280121-1129Automatic text summarizationExtractiveSystematic mappingGeneración automática de resúmenesExtractivoMapeo SistemáticoAutomatic Extractive Single Document Summarization: A Systematic MappingGeneración automática de resúmenes extractivos para un solo documento: un mapeo sistemáticoinfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a169http://purl.org/coar/version/c_970fb48d4fbd8a85Yip-Herrera, Juan-DavidMendoza-Becerra, Martha-ElianaRodríguez, Francisco-Javier001/14362oai:repositorio.uptc.edu.co:001/143622025-07-18 11:53:14.484metadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCrepositorio.uptc@uptc.edu.co |