Cargando…
Sentimental Analysis of COVID-19 Related Messages in Social Networks by Involving an N-Gram Stacked Autoencoder Integrated in an Ensemble Learning Scheme
The current population worldwide extensively uses social media to share thoughts, societal issues, and personal concerns. Social media can be viewed as an intelligent platform that can be augmented with a capability to analyze and predict various issues such as business needs, environmental needs, e...
Autores principales: | Kandasamy, Venkatachalam, Trojovský, Pavel, Machot, Fadi Al, Kyamakya, Kyandoghere, Bacanin, Nebojsa, Askar, Sameh, Abouhawwash, Mohamed |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8623208/ https://www.ncbi.nlm.nih.gov/pubmed/34833656 http://dx.doi.org/10.3390/s21227582 |
Ejemplares similares
-
Zero-Shot Human Activity Recognition Using Non-Visual Sensors
por: Al Machot, Fadi, et al.
Publicado: (2020) -
A Deep-Learning Model for Subject-Independent Human Emotion Recognition Using Electrodermal Activity Sensors
por: Al Machot, Fadi, et al.
Publicado: (2019) -
Blockchain-enabled K-harmonic framework for industrial IoT-based systems
por: Baalamurugan, K. M., et al.
Publicado: (2023) -
Document-Image Related Visual Sensors and Machine Learning Techniques
por: Kyamakya, Kyandoghere, et al.
Publicado: (2021) -
A Globally Generalized Emotion Recognition System Involving Different Physiological Signals
por: Ali, Mouhannad, et al.
Publicado: (2018)