Cargando…
Extracting Useful Emergency Information from Social Media: A Method Integrating Machine Learning and Rule-Based Classification
User-generated contents (UGCs) on social media are a valuable source of emergency information (EI) that can facilitate emergency responses. However, the tremendous amount and heterogeneous quality of social media UGCs make it difficult to extract truly useful EI, especially using pure machine learni...
Autores principales: | Shen, Hongzhou, Ju, Yue, Zhu, Zhijing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9915315/ https://www.ncbi.nlm.nih.gov/pubmed/36767235 http://dx.doi.org/10.3390/ijerph20031862 |
Ejemplares similares
-
Quantum computing and machine learning for Arabic language sentiment classification in social media
por: Omar, Ahmed, et al.
Publicado: (2023) -
An integrated method for cancer classification and rule extraction from microarray data
por: Huang, Liang-Tsung
Publicado: (2009) -
Discovering HIV related information by means of association rules and machine learning
por: Araujo, Lourdes, et al.
Publicado: (2022) -
Electron transfer rules of minerals under pressure informed by machine learning
por: Li, Yanzhang, et al.
Publicado: (2023) -
Development of a literature informed Bayesian machine learning method for feature extraction and classification
por: Madahian, Behrouz, et al.
Publicado: (2015)