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<Paper uid="W04-1215">
  <Title>Annotating Multiple Types of Biomedical Entities: A Single Word Classification Approach</Title>
  <Section position="5" start_page="80" end_page="82" type="concl">
    <SectionTitle>
4 Conclusion and Future work
</SectionTitle>
    <Paragraph position="0"> This paper presented the preliminary results of our study. We introduced the use of existing taggers and presented a way to collect common substrings shared by entities. Due to lack of time, the models were not well tuned against the two parameters - C and gamma, influencing the capabilities of the models. Further, not all of the training instances provided were used to train the model, and it will be interesting and worthwhile to investigate. How to deal with data imbalance is another important issue. By solving this problem, further evaluation of feature effectiveness would be facilitated. We believe there is much left for our approach to improve and it may perform better if more time is given.</Paragraph>
  </Section>
class="xml-element"></Paper>