ARIEX: Automated ranking of information extractors

Information extractors are used to transform the user-friendly information in a web document into structured information that can be used to feed a knowledge-based system. Researchers are interested in ranking them to find out which one performs the best. Unfortunately, many rankings in the literatu...

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Detalles Bibliográficos
Autores: Jiménez Aguirre, Patricia, Corchuelo Gil, Rafael, Sleiman, Hassan A.
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2016
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/131917
Acceso en línea:https://hdl.handle.net/11441/131917
https://doi.org/10.1016/j.knosys.2015.11.004
Access Level:acceso abierto
Palabra clave:Web documents
Information extraction
Ranking method
Automatisation
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spelling ARIEX: Automated ranking of information extractorsJiménez Aguirre, PatriciaCorchuelo Gil, RafaelSleiman, Hassan A.Web documentsInformation extractionRanking methodAutomatisationInformation extractors are used to transform the user-friendly information in a web document into structured information that can be used to feed a knowledge-based system. Researchers are interested in ranking them to find out which one performs the best. Unfortunately, many rankings in the literature are deficient. There are a number of formal methods to rank information extractors, but they also have many problems and have not reached widespread popularity. In this article, we present ARIEX, which is an automated method to rank web information extraction proposals. It does not have any of the problems that we have identified in the literature. Our proposal shall definitely help authors make sure that they have advanced the state of the art not only conceptually, but from an empirical point of view; it shall also help practitioners make informed decisions on which proposal is the most adequate for a particular problem.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-21744Ministerio de Economía, Industria y Competitividad TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-EMinisterio de Economía y Competitividad TIN2011-15497-EMinisterio de Economía y Competitividad TIN2013-40848-RElsevierLenguajes y Sistemas InformáticosTIC258: Data-centric Computing Research HubMinisterio de Educación y Ciencia (MEC). EspañaJunta de AndalucíaMinisterio de Ciencia e Innovación (MICIN). EspañaMinisterio de Economia, Industria y Competitividad (MINECO). EspañaMinisterio de Economía y Competitividad (MINECO). España2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/131917https://doi.org/10.1016/j.knosys.2015.11.004reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésKnowledge-Based Systems, 93 (February 2016), 84-108.TIN2007-64119P07-TIC-2602P08-TIC-4100TIN2008-04718-ETIN2010-21744TIN2010-09809-ETIN2010-10811-ETIN2010-09988-ETIN2011-15497-ETIN2013-40848-Rhttps://www.sciencedirect.com/science/article/pii/S0950705115004311?via%3Dihubinfo:eu-repo/semantics/openAccessoai:idus.us.es:11441/1319172026-06-17T12:51:07Z
dc.title.none.fl_str_mv ARIEX: Automated ranking of information extractors
title ARIEX: Automated ranking of information extractors
spellingShingle ARIEX: Automated ranking of information extractors
Jiménez Aguirre, Patricia
Web documents
Information extraction
Ranking method
Automatisation
title_short ARIEX: Automated ranking of information extractors
title_full ARIEX: Automated ranking of information extractors
title_fullStr ARIEX: Automated ranking of information extractors
title_full_unstemmed ARIEX: Automated ranking of information extractors
title_sort ARIEX: Automated ranking of information extractors
dc.creator.none.fl_str_mv Jiménez Aguirre, Patricia
Corchuelo Gil, Rafael
Sleiman, Hassan A.
author Jiménez Aguirre, Patricia
author_facet Jiménez Aguirre, Patricia
Corchuelo Gil, Rafael
Sleiman, Hassan A.
author_role author
author2 Corchuelo Gil, Rafael
Sleiman, Hassan A.
author2_role author
author
dc.contributor.none.fl_str_mv Lenguajes y Sistemas Informáticos
TIC258: Data-centric Computing Research Hub
Ministerio de Educación y Ciencia (MEC). España
Junta de Andalucía
Ministerio de Ciencia e Innovación (MICIN). España
Ministerio de Economia, Industria y Competitividad (MINECO). España
Ministerio de Economía y Competitividad (MINECO). España
dc.subject.none.fl_str_mv Web documents
Information extraction
Ranking method
Automatisation
topic Web documents
Information extraction
Ranking method
Automatisation
description Information extractors are used to transform the user-friendly information in a web document into structured information that can be used to feed a knowledge-based system. Researchers are interested in ranking them to find out which one performs the best. Unfortunately, many rankings in the literature are deficient. There are a number of formal methods to rank information extractors, but they also have many problems and have not reached widespread popularity. In this article, we present ARIEX, which is an automated method to rank web information extraction proposals. It does not have any of the problems that we have identified in the literature. Our proposal shall definitely help authors make sure that they have advanced the state of the art not only conceptually, but from an empirical point of view; it shall also help practitioners make informed decisions on which proposal is the most adequate for a particular problem.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/131917
https://doi.org/10.1016/j.knosys.2015.11.004
url https://hdl.handle.net/11441/131917
https://doi.org/10.1016/j.knosys.2015.11.004
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Knowledge-Based Systems, 93 (February 2016), 84-108.
TIN2007-64119
P07-TIC-2602
P08-TIC-4100
TIN2008-04718-E
TIN2010-21744
TIN2010-09809-E
TIN2010-10811-E
TIN2010-09988-E
TIN2011-15497-E
TIN2013-40848-R
https://www.sciencedirect.com/science/article/pii/S0950705115004311?via%3Dihub
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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