A coral-reef approach to extract information from HTML tables

Jiménez Aguirre, Patricia; Roldán Salvador, Juan Carlos; Corchuelo Gil, Rafael

doi:10.1016/j.asoc.2021.107980

Artículo

dc.creator	Jiménez Aguirre, Patricia	es
dc.creator	Roldán Salvador, Juan Carlos	es
dc.creator	Corchuelo Gil, Rafael	es
dc.date.accessioned	2022-04-08T10:53:08Z
dc.date.available	2022-04-08T10:53:08Z
dc.date.issued	2022
dc.identifier.citation	Jiménez Aguirre, P., Roldán Salvador, J.C. y Corchuelo Gil, R. (2022). A coral-reef approach to extract information from HTML tables. Applied Soft Computing, 115 (January 2022, art. nº107980)
dc.identifier.issn	1568-4946	es
dc.identifier.uri	https://hdl.handle.net/11441/131990
dc.description.abstract	his article presents Coraline, which is a new table-understanding proposal. Its novelty lies in a coral-reef optimisation algorithm that addresses the problem of feature selection in synchrony with a clustering technique and some custom heuristics that help extract information in a totally unsupervised manner. Our experimental analysis was performed on a large collection of tables with a variety of layouts, encoding problems, and formatting alternatives. Coraline could achieve an F1 score as high as 0.90 and took 7.07 CPU seconds per table, which improves on the best supervised proposal by 6.67% regarding effectiveness and 40.54% regarding efficiency; it also improves on the best unsupervised proposal by 11.11% regarding effectiveness while it remains very competitive regarding efficiency	es
dc.description.sponsorship	Ministerio de Ciencia e Innovación PID2020-112540RB-C44	es
dc.description.sponsorship	Junta de Andalucía P18-RT-1060	es
dc.format	application/pdf	es
dc.format.extent	9	es
dc.language.iso	eng	es
dc.publisher	Elsevier	es
dc.relation.ispartof	Applied Soft Computing, 115 (January 2022, art. nº107980)
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	HTML tables	es
dc.subject	Information extraction	es
dc.subject	Coral-reef optimisation	es
dc.subject	Feature selection	es
dc.subject	Clustering	es
dc.title	A coral-reef approach to extract information from HTML tables	es
dc.type	info:eu-repo/semantics/article	es
dc.type.version	info:eu-repo/semantics/submittedVersion	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.contributor.affiliation	Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos	es
dc.relation.projectID	PID2020-112540RB-C44	es
dc.relation.projectID	P18-RT-1060	es
dc.relation.publisherversion	https://www.sciencedirect.com/science/article/pii/S1568494621009029?via%3Dihub	es
dc.identifier.doi	10.1016/j.asoc.2021.107980	es
dc.contributor.group	Universidad de Sevilla. TIC258: Data-centric Computing Research Hub	es
dc.journaltitle	Applied Soft Computing	es
dc.publication.volumen	115	es
dc.publication.issue	January 2022, art. nº107980	es
dc.contributor.funder	Ministerio de Ciencia e Innovación (MICIN). España	es
dc.contributor.funder	Junta de Andalucía	es

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