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Cross-domain polarity classification using a knowledge-enhanced meta-classifier

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Cross-domain polarity classification using a knowledge-enhanced meta-classifier

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Franco-Salvador, M.; Cruz, FL.; Troyano Jiménez, JA.; Rosso, P. (2015). Cross-domain polarity classification using a knowledge-enhanced meta-classifier. Knowledge-Based Systems. 86:46-56. https://doi.org/10.1016/j.knosys.2015.05.020

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/63907

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Title: Cross-domain polarity classification using a knowledge-enhanced meta-classifier
Author: Franco-Salvador, Marc Cruz, Fermín L. Troyano Jiménez, José Antonio Rosso, Paolo
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
In this paper, we propose the use of meta-learning to combine and enrich those approaches by adding also other knowledge-based features. In addition to the aforementioned classical approaches, our system uses the BabelNet ...[+]
Subjects: Sentiment analysis , Cross-domain polarity classification , Meta-learning , Word sense disambiguation , Semantic network
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Knowledge-Based Systems. (issn: 0950-7051 )
DOI: 10.1016/j.knosys.2015.05.020
Publisher version: http://dx.doi.org/10.1016/j.knosys.2015.05.020
Project ID:
info:eu-repo/grantAgreement/MINECO//TIN2012-38536-C03-02/ES/ANALISIS DE CONTENIDOS GENERADOS POR USUARIOS/
info:eu-repo/grantAgreement/Junta de Andalucía//P11-TIC-7684 MO/ES/AORESCU Project/
European Commission WIQ-EI IRSES (No. 269180)
Description: "NOTICE: this is the author’s version of a work that was accepted for publication in Knowledge-Based Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in KNOWLEDGE-BASED SYSTEMS [Volume 86, September 2015, Pages 46–56] DOI http://dx.doi.org/10.1016/j.knosys.2015.05.020
This research has been carried out in the framework of the European Commission WIQ-EI IRSES (No. 269180) and DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) projects. This research ...[+]
Type: Artículo



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