Academic Journal
Transformer-based Multi-Task Learning for crisis actionability extraction
| العنوان: | Transformer-based Multi-Task Learning for crisis actionability extraction |
|---|---|
| المؤلفون: | ZHANG, Yuhao, LO, Siaw Ling, WIN MYINT, Phyo Yi |
| المصدر: | Research Collection School Of Computing and Information Systems |
| بيانات النشر: | Institutional Knowledge at Singapore Management University |
| سنة النشر: | 2023 |
| المجموعة: | Institutional Knowledge (InK) at Singapore Management University |
| مصطلحات موضوعية: | Actionability, Crisis response, Multi-Task Learning, Artificial Intelligence and Robotics, Social Media |
| الوصف: | Social media has become a valuable information source for crisis informatics. While various methods were proposed to extract relevant information during a crisis, their adoption by field practitioners remains low. In recent fieldwork, actionable information was identified as the primary information need for crisis responders and a key component in bridging the significant gap in existing crisis management tools. In this paper, we proposed a Crisis Actionability Extraction System for filtering, classification, phrase extraction, severity estimation, localization, and aggregation of actionable information altogether. We examined the effectiveness of transformer-based LSTM-CRF architecture in Twitter-related sequence tagging tasks and simultaneously extracted actionable information such as situational details and crisis impact via Multi-Task Learning. We demonstrated the system’s practical value in a case study of a real-world crisis and showed its effectiveness in aiding crisis responders with making well-informed decisions, mitigating risks, and navigating the complexities of the crisis. |
| نوع الوثيقة: | text |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | https://ink.library.smu.edu.sg/sis_research/8517; https://ink.library.smu.edu.sg/context/sis_research/article/9520/viewcontent/icis23_final_cam_ready__1_.pdf |
| الاتاحة: | https://ink.library.smu.edu.sg/sis_research/8517 https://ink.library.smu.edu.sg/context/sis_research/article/9520/viewcontent/icis23_final_cam_ready__1_.pdf |
| Rights: | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| رقم الانضمام: | edsbas.6C0CD84F |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |