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dc.contributor.authorGómez-Rodríguez, Carlos
dc.contributor.authorImran, Muhammad
dc.contributor.authorVilares, David
dc.contributor.authorSolera, Elena
dc.contributor.authorKellert, Olga
dc.date.accessioned2024-09-09T14:42:51Z
dc.date.available2024-09-09T14:42:51Z
dc.date.issued2024
dc.identifier.citationGómez-Rodríguez, C., Imran, M., Vilares, D., Solera, E., & Kellert, O. (2024). Dancing in the Syntax Forest: Fast, Accurate and Explainable Sentiment Analysis with SALSA. CEUR Workshop Proceedings. Vol. 3729, Pages 12 – 17. Seminar of the Spanish Society for Natural Language Processing: Projects and System Demonstrations, SEPLN-CEDI-PD 2024, A Coruna, June 2024es_ES
dc.identifier.issn1613-0073
dc.identifier.urihttp://hdl.handle.net/2183/38924
dc.descriptionIncluded in Proceedings of the Seminar of the Spanish Society for Natural Language Processing: Projects and System Demonstrations (SEPLN-CEDI-PD 2024) co-located with the 7th Spanish Conference on Informatics (CEDI 2024) A Coruña, Spain, June 19-20, 2024es_ES
dc.description.abstract[Abstract]: Sentiment analysis is a key technology for companies and institutions to gauge public opinion on products, services or events. However, for large-scale sentiment analysis to be accessible to entities with modest computational resources, it needs to be performed in a resource-efficient way. While some efficient sentiment analysis systems exist, they tend to apply shallow heuristics, which do not take into account syntactic phenomena that can radically change sentiment. Conversely, alternatives that take syntax into account are computationally expensive. The SALSA project, funded by the European Research Council under a Proof-of-Concept Grant, aims to leverage recently-developed fast syntactic parsing techniques to build sentiment analysis systems that are lightweight and efficient, while still providing accuracy and explainability through the explicit use of syntax. We intend our approaches to be the backbone of a working product of interest for SMEs to use in production.es_ES
dc.description.sponsorshipThis project has received funding by the European Research Council (ERC), under the Horizon Europe research and innovation programme (SALSA, grant agreement No 101100615).es_ES
dc.language.isoenges_ES
dc.publisherCEUR-WSes_ES
dc.relationinfo:eu-repo/grantAgreement/EC/HE/101100615es_ES
dc.relation.urihttps://ceur-ws.org/Vol-3729/p2_rev.pdfes_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rights© 2024 Copyright for this paper by its authors.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectOpinion mininges_ES
dc.subjectParsinges_ES
dc.subjectSentiment analysises_ES
dc.subjectSyntaxes_ES
dc.titleDancing in the Syntax Forest: Fast, Accurate and Explainable Sentiment Analysis with SALSAes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleCEUR Workshop Proceedingses_ES
UDC.volume3729es_ES
UDC.startPage12es_ES
UDC.endPage17es_ES
UDC.conferenceTitleSEPLN-CEDI-PD 2024 - Seminar of the Spanish Society for Natural Language Processing: Projects and System Demonstrations, co-located with the 7th Spanish Conference on Informatics (CEDI 2024)es_ES


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