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Conference Paper Severe Disease-Named Entity Recognition to Support Analysis of Korean Emergency Calls
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Authors
Hyunho Park, Eunjung Kwon, Minjung Lee, Sungwon Byon
Issue Date
2024-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2024, pp.703-705
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC62082.2024.10827738
Abstract
Named entity recognition (NER) helps to extract information from emergency calls (e.g., 119 calls in South Korea), thereby enabling the analysis of emergency situations. If nouns or clauses related to severe diseases can be recognized from emergency calls, it helps in assessing the severity of the emergency situations. This paper proposes severe disease-named entity recognition (SD-NER) that can detect nouns or clauses related to severe diseases and symptoms from Korean emergency calls. This paper also demonstrates the implementation of SD-NER using bidirectional encoder representations from transformers (BERT) embeddings and cosine similarity. SD-NER supports emergency call analysis by assessing the severity of the emergency situations, thus potentially mitigating the deterioration of emergency situations.
KSP Keywords
Cosine similarity, Named entity Recognition, South Korea, Support analysis, call analysis, emergency calls, emergency situation