Article ID Journal Published Year Pages File Type
10355620 Journal of Biomedical Informatics 2012 12 Pages PDF
Abstract
► Explored the use of distributional semantics for a sequence classification task such as concept extraction. ► Evaluated different distributional semantic models based on their ability to predict the semantic types of terms. ► Proposed semi supervised learning in a framework that is agnostic to the underlying supervised learning algorithm. ► Improved the F-score of a state of the art clinical concept extraction by 2%.
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
Authors
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