Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6928450 | Journal of Biomedical Informatics | 2014 | 8 Pages |
Abstract
- We explore estimating WSD performance on a range of ambiguous biomedical terms.
- We evaluate the difficulty predictions against the output of two WSD systems.
- Supervised methods are the best predictors but limited by labeled training data.
- Unsupervised methods all perform well and can be applied more widely.
- Best performance was obtained using the relatedness measure proposed by Lesk.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Bridget T. McInnes, Mark Stevenson,