Deep Bidirectional LSTM Network Learning-Based Sentiment Analysis for Arabic Text
Sentiment analysis aims to predict sentiment polarities (positive, negative or neutral) of a given piece of text. It lies at the intersection of many fields such as Natural Language Processing (NLP), Computational Linguistics, and Data Mining. Sentiments can be expressed explicitly or implicitly. Ar...
Guardado en:
Autores principales: | Elfaik Hanane, Nfaoui El Habib |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
De Gruyter
2020
|
Materias: | |
Acceso en línea: | https://doaj.org/article/fa571cada8a04ec6a4a35e910b9c9132 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Arabic sentiment analysis about online learning to mitigate covid-19
por: Ali Manal Mostafa
Publicado: (2021) -
Improving sentiment analysis in Arabic: A combined approach
por: Belgacem Brahimi, et al.
Publicado: (2021) -
BengSentiLex and BengSwearLex: creating lexicons for sentiment analysis and profanity detection in low-resource Bengali language
por: Salim Sazzed
Publicado: (2021) -
Deep Learning-based Sentiment Analysis and Topic Modeling on Tourism During Covid-19 Pandemic
por: Ram Krishn Mishra, et al.
Publicado: (2021) -
Improving Accuracy using The ASERLU layer in CNN-BiLSTM Architecture on Sentiment Analysis
por: Sandi Hermawan, et al.
Publicado: (2021)