A Knowledge-Rich Approach to Feature-Based Opinion Extraction from Product Reviews

Cruz Mata, Fermín; Troyano Jiménez, José Antonio; Enríquez de Salamanca Ros, Fernando; Ortega Rodríguez, Francisco Javier; García Vallejo, Carlos Antonio

doi:10.1145/1871985.1871990

Ponencia

dc.creator	Cruz Mata, Fermín	es
dc.creator	Troyano Jiménez, José Antonio	es
dc.creator	Enríquez de Salamanca Ros, Fernando	es
dc.creator	Ortega Rodríguez, Francisco Javier	es
dc.creator	García Vallejo, Carlos Antonio	es
dc.date.accessioned	2020-07-09T07:19:53Z
dc.date.available	2020-07-09T07:19:53Z
dc.date.issued	2010
dc.identifier.citation	Cruz Mata, F., Troyano Jiménez, J.A., Enríquez de Salamanca Ros, F., Ortega Rodríguez, F.J. y García Vallejo, C.A. (2010). A Knowledge-Rich Approach to Feature-Based Opinion Extraction from Product Reviews. En SMUC 2010: 2nd international workshop on Search and mining user-generated contents (13-20), Toronto, ON, Canada: ACM.
dc.identifier.isbn	978-1-4503-0386-6	es
dc.identifier.uri	https://hdl.handle.net/11441/99104
dc.description.abstract	Feature-based opinion extraction is a task related to infor- mation extraction, which consists of extracting structured opinions on features of some object from reviews or other subjective textual sources. Over the last years, this prob-lem has been studied by some researchers, generally in an unsupervised, domain-independent manner. As opposed to that, in this work we propose a rede nition of the problem from a more practical point of view, and describe a domain- speci c, resource-based opinion extraction system. We fo-cus on the description and generation of those resources, and brie y report the extraction system architecture and a few initial experiments. The results suggest that domain-speci c knowledge is a valuable resource in order to build precise opinion extraction systems.	es
dc.format	application/pdf	es
dc.format.extent	8	es
dc.language.iso	eng	es
dc.publisher	ACM	es
dc.relation.ispartof	SMUC 2010: 2nd international workshop on Search and mining user-generated contents (2010), p 13-20
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.title	A Knowledge-Rich Approach to Feature-Based Opinion Extraction from Product Reviews	es
dc.type	info:eu-repo/semantics/conferenceObject	es
dcterms.identifier	https://ror.org/03yxnpp24
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.publisherversion	https://dl.acm.org/doi/abs/10.1145/1871985.1871990	es
dc.identifier.doi	10.1145/1871985.1871990	es
dc.publication.initialPage	13	es
dc.publication.endPage	20	es
dc.eventtitle	SMUC 2010: 2nd international workshop on Search and mining user-generated contents	es
dc.eventinstitution	Toronto, ON, Canada	es
dc.relation.publicationplace	New York, USA	es

Ficheros	Tamaño	Formato	Ver	Descripción
A knowledge-rich approach to ...	1.102Mb	[PDF]	Ver/Abrir

Este registro aparece en las siguientes colecciones

Ponencias (Lenguajes y Sistemas Informáticos)

Mostrar el registro sencillo del ítem

Excepto si se señala otra cosa, la licencia del ítem se describe como: Attribution-NonCommercial-NoDerivatives 4.0 Internacional