Biomedical Term Recognition With the Perceptron HMM Algorithm
We propose a novel approach to
the identification of biomedical terms in research publications
using the Perceptron HMM algorithm.
Each important term is identified and classified into a biomedical
concept class. Our proposed system achieves a 68.6% F-measure based
on 2,000 training Medline abstracts and 404 unseen testing Medline
abstracts. The system achieves performance that is close to the
state-of-the-art using only a small feature set.
The Perceptron HMM algorithm provides
an easy way to incorporate many potentially interdependent features.