Early detection of emergency events from social media: a new text clustering approach.

Huang, Lida; Shi, Panpan; Zhu, Haichao; Chen, Tao

Huang, Lida; Shi, Panpan; Zhu, Haichao; Chen, Tao.

Afiliación

Huang L; Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing, 100084 China.
Shi P; Tsinghua-Gsafety Joint Institute of Public Safety and Emergency Technology Research, Gsafety Company, Beijing, 100094 China.
Zhu H; Tsinghua-Gsafety Joint Institute of Public Safety and Emergency Technology Research, Gsafety Company, Beijing, 100094 China.
Chen T; Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing, 100084 China.

Nat Hazards (Dordr) ; 111(1): 851-875, 2022.

Article en En | MEDLINE | ID: mdl-35095194

Palabras clave

BERT; Bi-LSTM; Early detection; Emergency event; Social media; Text clustering

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Screening_studies Idioma: En Revista: Nat Hazards (Dordr) Año: 2022 Tipo del documento: Article Pais de publicación: Países Bajos

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