한국어 읽기 텍스트 분류를 위한 오픈소스 인공지능 기술 성능 평가

• 영문명: Performance Evaluation of Open Source AI Technology for Korean Reading Text Classification
• 발행기관: 국제한국어교육학회
• 저자명: 김형민 고현준
• 간행물 정보: 『한국어교육』33권 2호, 115~135쪽, 전체 21쪽
• 주제분류: 어문학 > 한국어와문학
• 파일형태: PDF
• 발행일자: 2022.06.30

영문 초록

The purpose of this study is to evaluate the level of technical completeness of classifying text by subject through analysis of Korean natural language processing(NLP) open-source software related to the currently developed text classification. To this end, after searching for the released NLP software, the accuracy was evaluated using Naver news articles. As a result, it was analyzed that Simple RNN had an accuracy of 78% and LSTM of 80%. In addition, the model was evaluated using , and it was difficult to determine the accuracy because the training data was different from the evaluation data. However, if text classification technology is applied to Korean language education based on this study, the significance of this study can be found in that it is possible to efficiently manage vast amounts of Korean reading materials and provide texts tailored to learners’ interests.

목차

1. 서론

2. 텍스트 분류 인공지능 기술

3. 연구 내용 및 방법

4. 분석 결과

5. 결론

참고문헌

키워드

한국어 읽기 교육 텍스트 분류 자연어처리 성능 평가 Korean education of reading text classification natural language processing performance evaluation