CALA: An unsupervised URL-based web page classification system

Unsupervised web page classification refers to the problem of clustering the pages in a web site so that each cluster includes a set of web pages that can be classified using a unique class. The existing proposals to perform web page classification do not fulfill a number of requirements that would...

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Detalles Bibliográficos
Autores: Hernández Salmerón, Inmaculada Concepción, Rivero, Carlos R., Ruiz Cortés, David, Corchuelo Gil, Rafael
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2014
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/66444
Acceso en línea:http://hdl.handle.net/11441/66444
https://doi.org/10.1016/j.knosys.2013.12.019
Access Level:acceso abierto
Palabra clave:Web Page Classification
URL Classification
URL Patterns
Enterprise web information integration
Web Page Clustering
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spelling CALA: An unsupervised URL-based web page classification systemHernández Salmerón, Inmaculada ConcepciónRivero, Carlos R.Ruiz Cortés, DavidCorchuelo Gil, RafaelWeb Page ClassificationURL ClassificationURL PatternsEnterprise web information integrationWeb Page ClusteringUnsupervised web page classification refers to the problem of clustering the pages in a web site so that each cluster includes a set of web pages that can be classified using a unique class. The existing proposals to perform web page classification do not fulfill a number of requirements that would make them suitable for enterprise web information integration, namely: to be based on a lightweight crawling, so as to avoid interfering with the normal operation of the web site, to be unsupervised, which avoids the need for a training set of pre-classified pages, or to use features from outside the page to be classified, which avoids having to download it. In this article, we propose CALA, a new automated proposal to generate URL-based web page classifiers. Our proposal builds a number of URL patterns that represent the different classes of pages in a web site, so further pages can be classified by matching their URLs to the patterns. Its salient features are that it fulfills all of the previous requirements, and it has been validated by a number of experiments using real-world, top-visited web sites. Our validation proves that CALA is very effective and efficient in practice.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 Ciencia e Innovación TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-EMinisterio de Economía y Competitividad TIN2011-15497-EElsevierLenguajes y Sistemas InformáticosTIC134: Sistemas Informáticos2014info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/11441/66444https://doi.org/10.1016/j.knosys.2013.12.019reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésKnowledge-Based Systems, 57 (February 2014), 168-180.TIN2007-64119P07-TIC-2602P08-TIC-4100TIN2008-04718-ETIN2010-21744TIN2010-09809-ETIN2010-10811-ETIN2010-09988-ETIN2011-15497-Ehttp://www.sciencedirect.com/science/article/pii/S0950705113003997info:eu-repo/semantics/openAccessoai:idus.us.es:11441/664442026-06-17T12:51:07Z
dc.title.none.fl_str_mv CALA: An unsupervised URL-based web page classification system
title CALA: An unsupervised URL-based web page classification system
spellingShingle CALA: An unsupervised URL-based web page classification system
Hernández Salmerón, Inmaculada Concepción
Web Page Classification
URL Classification
URL Patterns
Enterprise web information integration
Web Page Clustering
title_short CALA: An unsupervised URL-based web page classification system
title_full CALA: An unsupervised URL-based web page classification system
title_fullStr CALA: An unsupervised URL-based web page classification system
title_full_unstemmed CALA: An unsupervised URL-based web page classification system
title_sort CALA: An unsupervised URL-based web page classification system
dc.creator.none.fl_str_mv Hernández Salmerón, Inmaculada Concepción
Rivero, Carlos R.
Ruiz Cortés, David
Corchuelo Gil, Rafael
author Hernández Salmerón, Inmaculada Concepción
author_facet Hernández Salmerón, Inmaculada Concepción
Rivero, Carlos R.
Ruiz Cortés, David
Corchuelo Gil, Rafael
author_role author
author2 Rivero, Carlos R.
Ruiz Cortés, David
Corchuelo Gil, Rafael
author2_role author
author
author
dc.contributor.none.fl_str_mv Lenguajes y Sistemas Informáticos
TIC134: Sistemas Informáticos
dc.subject.none.fl_str_mv Web Page Classification
URL Classification
URL Patterns
Enterprise web information integration
Web Page Clustering
topic Web Page Classification
URL Classification
URL Patterns
Enterprise web information integration
Web Page Clustering
description Unsupervised web page classification refers to the problem of clustering the pages in a web site so that each cluster includes a set of web pages that can be classified using a unique class. The existing proposals to perform web page classification do not fulfill a number of requirements that would make them suitable for enterprise web information integration, namely: to be based on a lightweight crawling, so as to avoid interfering with the normal operation of the web site, to be unsupervised, which avoids the need for a training set of pre-classified pages, or to use features from outside the page to be classified, which avoids having to download it. In this article, we propose CALA, a new automated proposal to generate URL-based web page classifiers. Our proposal builds a number of URL patterns that represent the different classes of pages in a web site, so further pages can be classified by matching their URLs to the patterns. Its salient features are that it fulfills all of the previous requirements, and it has been validated by a number of experiments using real-world, top-visited web sites. Our validation proves that CALA is very effective and efficient in practice.
publishDate 2014
dc.date.none.fl_str_mv 2014
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 http://hdl.handle.net/11441/66444
https://doi.org/10.1016/j.knosys.2013.12.019
url http://hdl.handle.net/11441/66444
https://doi.org/10.1016/j.knosys.2013.12.019
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Knowledge-Based Systems, 57 (February 2014), 168-180.
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
http://www.sciencedirect.com/science/article/pii/S0950705113003997
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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