Urdu Sentiment Analysis via Multimodal Data Mining Based on Deep Learning Algorithms
Every day, a massive amount of text, audio, and video data is published on websites all over the world. This valuable data can be used to gauge global trends and public perceptions. Companies are showcasing their preferred advertisements to consumers based on their online behavioral trends. Carefull...
Guardado en:
Autores principales: | Urooba Sehar, Summrina Kanwal, Kia Dashtipur, Usama Mir, Ubaid Abbasi, Faiza Khan |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/549a75538fd447709e4ae06590132c62 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Arabic Aspect-Based Sentiment Analysis: A Systematic Literature Review
por: Ruba Obiedat, et al.
Publicado: (2021) -
Improving sentiment analysis accuracy with emoji embedding
por: Chuchu Liu, et al.
Publicado: (2021) -
Targeted Aspect-Based Multimodal Sentiment Analysis: An Attention Capsule Extraction and Multi-Head Fusion Network
por: Donghong Gu, et al.
Publicado: (2021) -
Sentiment Analysis in Twitter Based on Knowledge Graph and Deep Learning Classification
por: Fernando Andres Lovera, et al.
Publicado: (2021) -
Improving Accuracy using The ASERLU layer in CNN-BiLSTM Architecture on Sentiment Analysis
por: Sandi Hermawan, et al.
Publicado: (2021)