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<Paper uid="W03-1713">
  <Title>News-Oriented Automatic Chinese Keyword Indexing</Title>
  <Section position="7" start_page="2" end_page="2" type="concl">
    <SectionTitle>
5 Conclusion and Future Work
</SectionTitle>
    <Paragraph position="0"> We have described a system for automatically indexing keywords from texts. One document is inputted into the recognizer module, the filter module and the selector module consecutively, with keywords output. Here we utilize the mature techniques available now such as string frequency statistics, segmentation and POS tagging tools.</Paragraph>
    <Paragraph position="1"> Then, according to features, we propose our method to evaluate directly every candidate key-word and select those with higher scores as keywords. At the same time, we break through the tradition of generating keywords only from the original text and acquire some keywords through looking up in the lexicon of content words with hierarchical relations. The experimental results show that our system can perform comparably to the state of the art.</Paragraph>
    <Paragraph position="2"> Owing to the limit of the training corpus, the parameters in scoring formula are set by experience values. With our method, we can cumulate more and more documents with keywords. Then we can adopt machine-learning methods to conduct keyword indexing, which can make parameters more objective. That will be our further work.</Paragraph>
  </Section>
class="xml-element"></Paper>