사용자 리뷰 분석을 통한 호텔 평가 항목별 누락 평점 예측 방법론

• 영문명: Predicting Missing Ratings of Each Evaluation Criteria for Hotel by Analyzing User Reviews
• 발행기관: 한국IT서비스학회
• 저자명: 이동훈(Donghoon Lee) 부현경(Hyunkyung Boo) 김남규(Namgyu Kim)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제16권 제4호, 161~176쪽, 전체 16쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2017.12.31

영문 초록

Recently, most of the users can easily get access to a variety of information sources about companies, products, and services through online channels. Therefore, the online user evaluations are becoming the most powerful tool to generate word of mouth. The user s evaluation is provided in two forms, quantitative rating and review text. The rating is then divided into an overall rating and a detailed rating according to various evaluation criteria. However, since it is a burden for the reviewer to complete all required ratings for each evaluation criteria, so most of the sites requested only mandatory inputs for overall rating and optional inputs for other evaluation criteria. In fact, many users input only the ratings for some of the evaluation criteria and the percentage of missed ratings for each criteria is about 40%. As these missed ratings are the missing values in each criteria, the simple average calculation by ignoring the average 40% of the missed ratings can sufficiently distort the actual phenomenon. Therefore, in this study, we propose a methodology to predict the rating for the missed values of each criteria by analyzing user s evaluation information included the overall rating and text review for each criteria. The experiments were conducted on 207,968 evaluations collected from the actual hotel evaluation site. As a result, it was confirmed that the prediction accuracy of the detailed criteria ratings by the proposed methodology was much higher than the existing average-based method.

목차

1. 서 론

2. 관련 연구

3. 리뷰 분석을 통한 세부 항목 누락 평점 예측 방법론

4. 실험

5. 결 론

키워드

Big Data Review Analysis Text Mining Topic Modeling