Serviços Personalizados
Journal
Artigo
Indicadores
- Citado por SciELO
- Acessos
Links relacionados
- Similares em SciELO
Compartilhar
Computación y Sistemas
versão On-line ISSN 2007-9737versão impressa ISSN 1405-5546
Resumo
PIRYANI, Rajesh; GUPTA, Vedika e SINGH, Vivek Kumar. Generating Aspect-based Extractive Opinion Summary: Drawing Inferences from Social Media Texts. Comp. y Sist. [online]. 2018, vol.22, n.1, pp.83-91. ISSN 2007-9737. https://doi.org/10.13053/cys-22-1-2784.
This paper presents an integrated framework to generate extractive aspect-based opinion summary from a large volume of free-form text reviews. The framework has three major components: (a) aspect identifier to determine the aspects in a given domain; (b) sentiment polarity detector for computing the sentiment polarity of opinion about an aspect; and (c) summary generator to generate opinion summary. The framework is evaluated on SemEval-2014 dataset and obtains better results than several other approaches.
Palavras-chave : Aspect-level sentiment analysis; laptop; polarity; sentiment summarization; big data.