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Evolutionary Neural Architecture Search (NAS) Using Chromosome Non-Disjunction for Korean Grammaticality Tasksopen access

Authors
Park, Kang-moonShin, DonghoonYoo, Yongsuk
Issue Date
May-2020
Publisher
MDPI
Keywords
Deep learning; Korean syntax; Neural architecture search; Word ordering
Citation
Applied Sciences-basel, v.10, no.10
Journal Title
Applied Sciences-basel
Volume
10
Number
10
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/151523
DOI
10.3390/app10103457
ISSN
2076-3417
Abstract
Featured Application,Neural Architecture Search (NAS) on linguistic tasks.,Abstract In this paper, we apply the neural architecture search (NAS) method to Korean grammaticality judgment tasks. Since the word order of a language is the final result of complex syntactic operations, a successful neural architecture search in linguistic data suggests that NAS can automate language model designing. Although NAS application to language has been suggested in the literature, we add a novel dataset that contains Korean-specific linguistic operations, which adds great complexity in the patterns. The result of the experiment suggests that NAS provides an architecture for the language. Interestingly, NAS has suggested an unprecedented structure that would not be designed manually. Research on the final topology of the architecture is the topic of our future research.,
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공과대학 > 기계시스템학부 > 1. Journal Articles

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