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<Paper uid="W06-2203">
  <Title>References</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
References
</SectionTitle>
    <Paragraph position="0"> F. Ciravegna. 2001. Adaptive information extraction from text by rule induction and generalisation. IJCAI.</Paragraph>
    <Paragraph position="1"> N. Cristianini and J. Shawe-Taylor. 2000. An introduction to support vector machines and other kernel based methods. Cambridge Univ. Press. A. Finn and N. Kushmerick. 2004. Multi-level boundary classification for information extraction. Proc. 15th european conference on machine learning. D. Freitag. 1998. Machine learning for information extraction in informal domains. PhD thesis, Carnegie Mellon Univ.</Paragraph>
    <Paragraph position="2"> D. Freitag and N. Kushmerick. 2000. Boosted wrapper induction. AAAI.</Paragraph>
    <Paragraph position="3"> A. Gliozzo et al. 2005. Instance filtering for entity recognition. ACM SIGKDD explorations special issue on natural language processing and text mining. A. Lavelli et al. 2004. A critical survey of the methodology for IE evaluation. LREC.</Paragraph>
    <Paragraph position="4"> Y. Li et al. 2005. SVM based learning system for information extraction. Proc. of Sheffield Machine Learning Workshop.</Paragraph>
    <Paragraph position="5"> N. Ireson et al. Evalutating machine learning for information extraction. ICML.</Paragraph>
    <Paragraph position="6"> J. Iria. 2005. Relation extraction for mining the semantic web. Dagstuhl seminar on machine learning for the semantic web.</Paragraph>
    <Paragraph position="7"> J. Mayfield et al. 2003. Named entity recognition using hundreds of thousands of features. CoNLL.</Paragraph>
    <Paragraph position="8"> F. Sebastiani. 1999. Machine learning in automated text categorization. ACM computing surveys.</Paragraph>
  </Section>
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