Prominent Feature Extraction for Sentiment Analysis

The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Agarwal, Basant (Autor), Mittal, Namita (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Socio-Affective Computing,
Temas:
Neurosciences.
Natural language processing (Computer science).
Computational linguistics.
Data mining.
Application software.
Social sciences-Data processing.
Neuroscience.
Natural Language Processing (NLP).
Computational Linguistics.
Data Mining and Knowledge Discovery.
Computer and Information Systems Applications.
Computer Application in Social and Behavioral Sciences.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction
  • Literature Survey
  • Machine Learning Approach for Sentiment Analysis
  • Semantic Parsing using Dependency Rules
  • Sentiment Analysis using ConceptNet Ontology and Context Information
  • Semantic Orientation based Approach for Sentiment Analysis
  • Conclusions and FutureWork
  • References
  • Glossary
  • Index.

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