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CS372 Natural Language Processing with Python, Project, 2020 Spring

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SinK-DaT (Sino-Korean Detector and Translator)

CS372 Natural Language Processing with Python, Project, 2020 Spring

Mina Huh, Seokjun Kim, Jeongeon Park, Juhoon Lee, Hyunchang Oh

Abstract

We introduce a new Korean language model called SinK-DaT, the Sino-Korean (Sin-Ko) Detector and Translator. SinK-DaT provides the correct meaning and Chinese character representations of the ”difficult” Sin-Ko word based on context from a given Korean text. Experiments on old Korean news articles show that the model can not only detect most SinKo words, but also distinguish difficult ones among the detected Sin-Ko words and thus, supply the most suitable definitions to the users. As a result, Sink-DaT helps the young Korean generation in comprehending difficult corpora.

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CS372 Natural Language Processing with Python, Project, 2020 Spring

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