Hybrid models for sense guessing of Chinese unknown words
2008 ◽
Vol 13
(1)
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pp. 99-128
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Keyword(s):
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.
2014 ◽
Vol 20
(4)
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pp. 675-704
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2019 ◽
pp. 654-680
Keyword(s):
2019 ◽
Vol 22
(3)
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pp. 365-380
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Keyword(s):
Keyword(s):
2021 ◽
Vol ahead-of-print
(ahead-of-print)
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2020 ◽
Vol 22
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pp. 1-22
Keyword(s):
2015 ◽
Vol 20
(3)
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pp. 305-323
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