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텍스트 마이닝 기법을 통한 일본어능력시험 분석과 학습 교육 ―JLPT 4급 문자・어휘를 중심으로―

Analysis of the Japanese Language Proficiency Test and Teaching and Learning trough Text Mining Techniques: JLPT Level 4 Vocabulary

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참고문헌

키워드

주제분류일본어와문학

초록

本研究では、Python3.8、Janome・MeCab形態素分析器、Seaborn, Wordcloudツールを用いて、JLPT4級(N4)既出文字・語彙の頻出キーワード、頻度数、形態素を抽出した。また、このようなテキストマイニングによるトレンド分析と予測を試み、文字語彙の教育・学習方法を提案した。その結果は、次のとおりである。 (1)4級において、2回以上頻出した単語は計431個となった。この中で3回以上出現した上位キーワード・272個をデータベース化し、視覚的に提示した。(2)431個は、類似表現の出現割合が高く、ペアで頻出する傾向を呈しているが、この中で44個のグループをデータ作成した。(3)文字語彙に多出する文法表現・11個を抽出のうえデータを作成し、(4)頻出する上・下位語、反意語、自・他動詞の傾向を明らかにした。(5)形態素分析の結果、名詞(50.2%)、動詞(25.4%)のシェアが約75%にのぼることが分かった。(6)Wordnetは、類義語と上・下位語の教育、トリリングガルのための語彙力の向上やカスタム教育のための効果的なツールとして提案できるだろう。

Abstract

The purpose of this study was to extract keywords, frequencies, and morphemes from the characters and vocabulary used in the JLPT level 4. Moreover, this study aimed to analyze trends and make future predictions by conducting text mining analysis through the Python 3.8 program, Janome and Mecab morpheme analyzers, and Seaborn and Wordcloud library. The text mining analysis results are as follows: (1) In N4, a total of 431 words were extracted and noted as occurring more than two times. Among these words, 272 key words were extracted more than three times and were built into the database and presented visually. (2) A total of 431 words showed high occurrence of similar expressions and a trend of frequent occurrence in pairs. The database divided these into 44 groups. (3) A total of 11 grammatical expressions appearing frequently in terms of character and vocabulary were input in the database. (4) Hypernyms and hyponyms, antonyms, and transitive and intransitive verb pairs appeared frequently. (5) The morpheme analysis results show that the percentage of nouns (50.2%) and verbs (25.4%) was approximately 75%, thereby introducing the possibility of expanding the amount of basic vocabulary learned by understanding the flow of importance leading to verbs and other adjectives, centered on Chinese nouns. (6) The Wordnet tool can be used for learning synonyms, hypernyms, and hyponyms, as well as for developing trilingual customized education. Moreover, this tool can be used to ensure effective language learning and provide useful teaching methods for improving vocabulary in the three languages.

참고문헌 (15)

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