웹 데이터 마이닝 기법을 이용한 레스토랑 만족도 평가에 관한 연구 -네이버 윙스푼 데이터 분석

• 발행기관: 한국외식경영학회
• 저자명: 도해용(Hae Yong Do) 이애주(Ae Joo Lee) 강한훈(Han Hoon Kang)
• 간행물 정보: 『외식경영연구』15권 2호, 115~131쪽, 전체 17쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2012.04.30

영문 초록

The purpose of this study is to provide a useful research result for a restaurant owner who establishes a business with little capital as well as for a Web & App based LBS service company who is unfamiliar with the restaurant industry, This study used the Specific Web data-mining crawler to collect 22,440 of restaurant customer reviews from internet restaurant rating services such as Wingspoon in naver.com. The collected reviews were analyzed in terms of satisfaction in food, service, mood, and overall satisfaction, in consideration of restaurant locations, types, and the number of evaluations. Among the listed satisfaction factors, food was shown to be the dominant factor followed by service in the second and mood in the third influential factor in determination of the overall satisfaction. This research based on customer``s internet reviews of restaurants confirms and demonstrates that food is the most important factor in restaurant rating and in choice of a next place for dining.

키워드

Web data mining Restaurant rating site Customer satisfaction LBS Location based service