사용자 의견 추출을 위한 텍스트 마이닝 기반 비정형 데이터 정량화 방안

• 영문명: Unstructured Data Quantification Scheme Based on Text Mining for User Feedback Extraction
• 발행기관: 한국산업경영시스템학회
• 저자명: 조중흠(Jung-Heum Jo) 정용택(Yong-Taek Chung) 최성욱(Seong-Wook Choi) 옥창수(Changsoo Ok)
• 간행물 정보: 『산업경영시스템학회지』제41권 제4호, 131~137쪽, 전체 7쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2018.12.30

영문 초록

People write reviews of numerous products or services on the Internet, in their blogs or community bulletin boards. These unstructured data contain important emotions and opinions about the author s product or service, which can provide important information for future product design or marketing. However, this text-based information cannot be evaluated quantitatively, and thus they are difficult to apply to mathematical models or optimization problems for product design and improvement. Therefore, this study proposes a method to quantitatively extract user’s opinion or preference about a specific product or service by utilizing a lot of text-based information existing on the Internet or online. The extracted unstructured text information is decomposed into basic unit words, and positive rate is evaluated by using existing emotional dictionaries and additional lists proposed in this study. This can be a way to effectively utilize unstructured text data, which is being generated and stored in vast quantities, in product or service design. Finally, to verify the effectiveness of the proposed method, a case study was conducted using movie review data retrieved from a portal website. By comparing the positive rates calculated by the proposed framework with user ratings for movies, a guideline on text mining based evaluation of unstructured data is provided.

목차

1. 서 론

2. 텍스트 마이닝을 활용한 비정형 데이터 분석

3. 비정형 데이터 정량화 프레임 워크

4. 사례 연구 : 영화 리뷰(댓글) 감성 분석

5. 실험 결과

6. 결 론

키워드

Text Mining Sentiment Analysis Unstructured Data Movie Review Evaluation Framework