Semantic and Morpho-Syntactic Prevention’s Guidelines for COVID-19 Based on Cognitively Inspired Artificial Intelligence and Data Mining. Case Study: Europe, North America, and South America
Based on a combination of cognitively inspired methods in artificial intelligence such as artificial mathematical intelligence and data mining, we study the correlation between the COVID-19 pandemic and the sentiment analysis (qualitative ontological nature) of tweets and their linguistic patterns f...
- Autores:
-
Herrera Jaramillo, Yoe Alexander
Gómez Ramírez, Danny Arlen de Jesús
Ortega Giraldo, Johana C.
Ardila García, Alex M.
- Tipo de recurso:
- Part of book
- Fecha de publicación:
- 2021
- Institución:
- Tecnológico de Antioquia
- Repositorio:
- Repositorio Tdea
- Idioma:
- eng
- OAI Identifier:
- oai:dspace.tdea.edu.co:tdea/2888
- Acceso en línea:
- https://dspace.tdea.edu.co/handle/tdea/2888
- Palabra clave:
- Minería de datos
Data mining
Fouille de données
COVID-19
tweeter
Sentimiento
Feeling
Sentiment
Sentimento
Inteligencia artificial
Intelligence artificielle
Artificial intelligence
- Rights
- closedAccess
- License
- http://purl.org/coar/access_right/c_14cb