Hybrid models for sense guessing of Chinese unknown words
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.
Cited by 2 other publications
. Summary and Outlook
. In Computational Methods for Corpus Annotation and Analysis
pp. 175 ff.
Lu, Xiaofei & Renfen Hu
. Sense-aware lexical sophistication indices and their relationship to second language writing quality
. Behavior Research Methods
pp. 1444 ff.
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