Automatic Extraction of Collocations from Korean Text

In this paper, we propose a statistical method to automatically extract collocations from Korean POS-tagged corpus. Since a large portion of language is represented by collocation patterns, the collocational knowledge provides a valuable resource for NLP applications. One difficulty of collocation e...

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Bibliographic Details
Published in:Computers and the humanities 2001-08, Vol.35 (3), p.273-297
Main Authors: Kim, Seonho, Yoon, Juntae, Song, Mansuk
Format: Article
Language:English
Subjects:
Alcohol drinking
Collocations
Computer science
Construction materials industry
Industrial products
Korean language
Language
Linguistics
Mathematics and linguistics
Statistical methods
Textile industry
Textual collocation
Timber industry
Transportation industries
Trucking industry
Wine industry
Words
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Summary:In this paper, we propose a statistical method to automatically extract collocations from Korean POS-tagged corpus. Since a large portion of language is represented by collocation patterns, the collocational knowledge provides a valuable resource for NLP applications. One difficulty of collocation extraction is that Korean has a partially free word order, which also appears in collocations. In this work, we exploit four statistics, 'frequency', 'randomness', 'convergence', and 'correlation' in order to take into account the flexible word order of Korean collocations. We separate meaningful bigrams using an evaluation function based on the four statistics and extend the bigrams to n-gram collocations using a fuzzy relation. Experiments show that this method works well for Korean collocations.
ISSN:0010-4817
1574-020X
1572-8412
1574-0218
DOI:10.1023/A:1017507019909