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Multilingual Epidemiological Text Classification: A Comparative Study
2021
Zenodo
In this paper, we approach the multilingual text classification task in the context of the epidemiological field. Multilingual text classification models tend to perform differently across different languages (low- or high-resourced), more particularly when the dataset is highly imbalanced, which is the case for epidemiological datasets. We conduct a comparative study of different machine and deep learning text classification models using a dataset comprising news articles related to epidemic
doi:10.5281/zenodo.4476039
fatcat:cnudnstepzbvbgb3g6yy2uwrji