딥러닝을 활용한 고객 경험 기반 상품 평가 변화 예측 방법론

• 영문명: A Methodology for Predicting Changes in Product Evaluation Based on Customer Experience Using Deep Learning
• 발행기관: 한국IT서비스학회
• 저자명: 안지예(Jiyea An) 김남규(Namgyu Kim)
• 간행물 정보: 『한국IT서비스학회지』제21권 제4호, 75~90쪽, 전체 16쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2022.08.31

영문 초록

From the past to the present, reviews have had much influence on consumers' purchasing decisions. Companies are making various efforts, such as introducing a review incentive system to increase the number of reviews. Recently, as various types of reviews can be left, reviews have begun to be recognized as interesting new content. This way, reviews have become essential in creating loyal customers. Therefore, research and utilization of reviews are being actively conducted. Some studies analyze reviews to discover customers' needs, studies that upgrade recommendation systems using reviews, and studies that analyze consumers' emotions and attitudes through reviews. However, research that predicts the future using reviews is insufficient. This study used a dataset consisting of two reviews written in pairs with differences in usage periods. In this study, the direction of consumer product evaluation is predicted using KoBERT, which shows excellent performance in Text Deep Learning. We used 7,233 reviews collected to demonstrate the excellence of the proposed model. As a result, the proposed model using the review text and the star rating showed excellent performance compared to the baseline that follows the majority voting.

목차

1. 서 론

2. 선행 연구

3. 제안 연구

4. 실 험

5. 결 론

참고문헌

키워드

Deep learning BERT Review Analysis Future Prediction Text Classification Customer Experience