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Indonesian disaster named entity recognition from multi source information using bidirectional LSTM (BiLSTM)

Precise logistic support is essential after a disaster occurs. It must be timely, accurate, targeted, and based on existing needs. However, obtaining sufficient and accurate information related to logistic distribution locations remains a key problem. Therefore, implementing Named Entity Recognition...

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Asıl Yazarlar: Guruh Fajar Shidik, Filmada Ocky Saputra, Galuh Wilujeng Saraswati, Nurul Anisa Sri Winarsih, Muhammad Syaifur Rohman, Ricardus Anggi Pramunendar, Edi Jaya Kusuma, Danny Oka Ratmana, Valentijn Venus, Pulung Nurtantio Andono, Zainal Arifin Hasibuan
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: Elsevier 2024-09-01
Seri Bilgileri:Journal of Open Innovation: Technology, Market and Complexity
Konular:
Disaster emergency information
Named entity recognition
Deep learning
BiLSTM networks
Random oversampling
Online Erişim:http://www.sciencedirect.com/science/article/pii/S2199853124001525
Etiketler: Etiketle
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