Hierarchical Attention Network를 활용한 주제에 따른 온라인 고객 리뷰 분석 모델

• 영문명: Analysis of the Online Review Based on the Theme Using the Hierarchical Attention Network
• 발행기관: 한국IT서비스학회
• 저자명: 장인호(In Ho Jang) 박기연(Ki Yeon Park) 이준기(Zoon Ky Lee)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제17권 제2호, 165~177쪽, 전체 13쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2018.06.30

영문 초록

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer s purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

목차

1. 서 론

2. 이론적 배경

3. 연구 방법

4. 연구 결과

5. 결 론

References

About the Authors

키워드

Deep Learning Hierarchical Attention Network Online Market Online Customer Review Web Text Analysis