1887
Volume 13, Issue 1
  • ISSN 1384-6655
  • E-ISSN: 1569-9811
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Abstract

This paper addresses the problem of classifying Chinese unknown words into fine-grained semantic categories defined in a Chinese thesaurus, Cilin (Mei et al. 1984). We present three novel knowledge-based models that capture the relationship between the semantic categories of an unknown word and those of its component characters in three different ways, and combine two of them with a corpus-based model that uses contextual information to classify unknown words. Experiments show that the combined knowledge-based model outperforms previous methods on the same task, but the use of contextual information does not further improve performance.
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/content/journals/10.1075/ijcl.13.1.06lu
2008-01-01
2019-10-19
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References

http://instance.metastore.ingenta.com/content/journals/10.1075/ijcl.13.1.06lu
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