Hybrid models for sense guessing 866 of Chinese unknown words

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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.

Original languageEnglish (US)
Pages (from-to)99-128
Number of pages30
JournalInternational Journal of Corpus Linguistics
Issue number1
StatePublished - 2008

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language


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