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Automatic Extraction of Collocations From Korean Text

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Abstract

In this paper, we propose a statistical method to automaticallyextract 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.

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Authors and Affiliations

  1. Department of Computer Science, College of Engineering, Yonsei University, Seoul, 120-749, Korea

    Seonho Kim, Juntae Yoon & Mansuk Song

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  1. Seonho Kim
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  2. Juntae Yoon
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  3. Mansuk Song
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Kim, S., Yoon, J. & Song, M. Automatic Extraction of Collocations From Korean Text. Computers and the Humanities 35, 273–297 (2001). https://doi.org/10.1023/A:1017507019909

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