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<Paper uid="N04-2002">
  <Title>Identifying Chemical Names in Biomedical Text: An Investigation of the Substring Co-occurrence Based Approaches</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We investigate various strategies for finding chemicals in biomedical text using substring co-occurrence information. The goal is to build a system from readily available data with minimal human involvement. Our models are trained from a dictionary of chemical names and general biomedical text.</Paragraph>
    <Paragraph position="1"> We investigated several strategies including Naive Bayes classifiers and several types of N-gram models. We introduced a new way of interpolating N-grams that does not require tuning any parameters. We also found the task to be similar to Language Identification.</Paragraph>
  </Section>
class="xml-element"></Paper>