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<Paper uid="W00-1214">
  <Title>Machine Learning Methods for Chinese Web Page Categorization</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper reports our evaluation of k Nearest Neighbor (kNN), Support Vector Machines (SVM), and Adaptive Resonance Associative Map (ARAM) on Chinese web page classification. Benchmark experiments based on a Chinese web corpus showed that their predictive performance were roughly comparable although ARAM and kNN slightly outperformed SVM in small categories. In addition, inserting rules into ARAM helped to improve performance, especially for small well-defined categories.</Paragraph>
  </Section>
class="xml-element"></Paper>