Papers with ML approaches

2 papers
Annotation of a Large Clinical Entity Corpus (D18-1)

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Challenge: Past researches have shown the superiority of statistical/ML approaches over the rule based approaches.
Approach: They propose to annotate a clinical domain annotated corpus using a small data set or a narrower domain to take full advantage of machine learning.
Outcome: The proposed corpus contains 5,160 clinical documents from forty different clinical specialties.
Weak Supervision for Learning Discourse Structure (D19-1)

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Challenge: a weak supervision approach is a promising tool for learning discourse structure for multi-party dialogue.
Approach: They propose a data programming paradigm that allows a user to label training data using expert-composed heuristics and transform them into probability distributions of the class labels.
Outcome: The proposed approach outperforms both deep learning and traditional ML approaches on the task of learning discourse structure for multi-party dialogue.

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