• Smart Media Journal
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• v.9 no.4
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• pp.144-151
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• 2020

In a mobile environment, communication takes place via SMS text messages. Vocabularies used in SMS texts can be expected to use vocabularies of different classes from those used in general Korean literary style sentence. For example, in the case of a typical literary style, the sentence is correctly initiated or terminated and the sentence is well constructed, while SMS text corpus often replaces the component with an omission and a brief representation. To analyze these vocabulary usage characteristics, the existing colloquial style corpus and the literary style corpus are used. The experiment compares and analyzes the vocabulary use characteristics of the colloquial corpus SMS text corpus and the Naver Sentiment Movie Corpus, and the written Korean written corpus. For the comparison and analysis of vocabulary for each corpus, the part of speech tag adjective (VA) was used as a standard, and a distinctive collexeme analysis method was used to measure collostructural strength. As a result, it was confirmed that adjectives related to emotional expression such as'good-','sorry-', and'joy-' were preferred in the SMS text corpus, while adjectives related to evaluation expressions were preferred in the Naver Sentiment Movie Corpus. The word embedding was used to automatically construct a sentiment lexicon based on the extracted adjectives with high collostructural strength, and a total of 343,603 sentiment representations were automatically built.

• Korean Linguistics
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• v.64
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• pp.195-223
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• 2014

The aim of this paper is to study the morphemization of {Geuraegajigo} based on a spontaneous speech corpus. For this purpose, the distributions, the semantic functions, and the intonational phrase pattterns of the connective {Geuraegajigo} have been analyzed based on the corpus. The results are as follow; at first, coalescence that comes with a morphemization process was found, resulting in many variations. Secondly, there are three functions of it: [Direct/Indirect interrelationship], [Enumerate conjunction], and [Discourse marker]. And this semantic/functional diversity has many similarities with conjunctive adverbs. Lastly, intonational phrase patterns of {Geuraegajigo} accord with those of conjunctive adverbs. Especially, the discourse strategic IP pattern is connected with the short variation type. In conclusion, {Geuraegajigo} has finished turning into a conjunctive adverb through morphemization.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.271-277
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• 2020

Machine translation refers to software that translates a source language into a target language, and has been actively researching Neural Machine Translation through rule-based and statistical-based machine translation. One of the important factors in the Neural Machine Translation is to extract high quality parallel corpus, which has not been easy to find high quality parallel corpus of Korean language pairs. Recently, the AI HUB of the National Information Society Agency(NIA) unveiled a high-quality 1.6 million sentences Korean-English parallel corpus. This paper attempts to verify the quality of each data through performance comparison with the data published by AI Hub and OpenSubtitles, the most popular Korean-English parallel corpus. As test data, objectivity was secured by using test set published by IWSLT, official test set for Korean-English machine translation. Experimental results show better performance than the existing papers tested with the same test set, and this shows the importance of high quality data.

• Journal of KIISE
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• v.43 no.1
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• pp.71-79
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• 2016

Disambiguation of homographs is an important job in Korean semantic processing and has been researched for long time. Recently, machine learning approaches have demonstrated good results in accuracy and speed. Other knowledge-based approaches are being researched for untrained words. This paper proposes a hybrid method based on the machine learning approach that uses a lexical semantic network. The use of a hybrid approach creates an additional corpus from subcategorization information and trains this additional corpus. A homograph tagging phase uses the hypernym of the homograph and an additional corpus. Experimentation with the Sejong Corpus and UWordMap demonstrates the hybrid method is to be effective with an increase in accuracy from 96.51% to 96.52%.

• Cross-Cultural Studies
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• v.37
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• pp.309-334
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• 2014

This study is based on the Korean-Chinese parallel corpus, utilizing the Korean connective morpheme '-myenseo' and contrasting with the Chinese expression. Korean learners often struggle with the use of Korean Connective Morpheme especially when there is a lexical gap between their mother language. '-myenseo' is of the most use Korean Connective Morpheme, it usually contrast to the Chinese coordinating conjunction. But according to the corpus, the contrastive Chinese expression to '-myenseo' is more than coordinating conjunction. So through this study, can help the Chinese Korean language learners learn easier while studying '-myenseo', because the variety Chinese expression are found from the parallel corpus that related to '-myenseo'. In this study, firstly discussed the semantic features and syntactic characteristics of '-myenseo'. The significant semantic features of '-myenseo' are 'simultaneous' and 'conflict'. So in this chapter the study use examples of usage to analyse the specific usage of '-myenseo'. And then this study analyse syntactic characteristics of '-myenseo' through the subject constraint, predicate constraints, temporal constraints, mood constraints, negatives constraints. then summarize them into a table. And the most important part of this study is Chapter 4. In this chapter, it contrasted the Korean connective morpheme '-myenseo' to the Chinese expression by analysing the Korean-Chinese parallel corpus. As a result of the analysis, the frequency of the Chinese expression that contrasted to '-myenseo' is summarized into