Generating Aspect-based Extractive Opinion Summary: Drawing Inferences from Social Media Texts
Título del documento: Generating Aspect-based Extractive Opinion Summary: Drawing Inferences from Social Media Texts
Revue: Computación y sistemas
Base de datos: PERIÓDICA
Número de sistema: 000423266
ISSN: 1405-5546
Autores: 1
2
3
Instituciones: 1South Asian University, Department of Computer Science, Nueva Delhi, Delhi. India
2National Institute of Technology Delhi, Department of Computer Science, Delhi, Haryana. India
3Banaras Hindu University, Department of Computer Science, Varanasi, Uttar Pradesh. India
Año:
Periodo: Ene-Mar
Volumen: 22
Número: 1
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Aplicado, descriptivo
Resumen en inglés 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
Disciplinas: Bibliotecología y ciencia de la información
Palabras clave: Análisis y sistematización de la información,
Análisis de textos,
Redes sociales,
Análisis de opinión,
Sentimientos,
Big data
Keyword: Information analysis,
Text analysis,
Social networks,
Opinion analysis,
Feelings,
Big data
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