Papers by Moses Odeo

2 papers
A Dataset for Multi-lingual Epidemiological Event Extraction (2020.lrec-1)

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Challenge: Using the Web, we propose a corpus for information extraction and text classification.
Approach: They propose to use a corpus for information extraction and natural language processing (NLP) tasks such as text classification.
Outcome: The proposed corpus can be used for information extraction and natural language processing tasks such as text classification.
Multilingual Epidemiological Text Classification: A Comparative Study (2020.coling-main)

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Challenge: a comparative study of multilingual text classification models analyzes the performance of different models based on different languages . low-resource languages are highly influenced by typology of the languages on which the models have been trained or fine-tuned but also by their size.
Approach: They compare machine and deep learning models with a dataset of epidemiological news articles . they find that the performance of the models is proportionate to the training data size .
Outcome: The proposed model outperforms baseline models on a multilingual text classification task . low-resource languages are highly influenced by typology of languages and their size .

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