<?xml version="1.0" standalone="yes"?>
<Paper uid="W06-3319">
  <Title>Biomedical Term Recognition With the Perceptron HMM Algorithm</Title>
  <Section position="4" start_page="114" end_page="114" type="concl">
    <SectionTitle>
3 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have proposed a new approach to the biomedical term recognition task using the Perceptron HMM algorithm. Our proposed system achieves a 68.6% F-measure with a relatively small number of features as compared to the systems of the JNLPBA participants. The Perceptron HMM algorithm is much easier to implement than the SVM-HMMs, CRF, and the Maximum Entropy Markov Models, while the performance is comparable to those approaches. In the future, we plan to experiment with incorporating external resources, such as dictionaries and gene ontologies, into our feature set.</Paragraph>
  </Section>
class="xml-element"></Paper>