메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Shadiyar Aralbayeva (Kyungsung University) Shuting Tao (Kyungsung University) Hak-Seon Kim (Kyungsung University)
저널정보
한국조리학회 Culinary Science & Hospitality Research Culinary Science & Hospitality Research Vol.24 No.7(Wn.98)
발행연도
2018.9
수록면
109 - 118 (10page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
The purpose of this study was to compare the restaurant industries between Seoul and Busan through the semantic network analysis of big data by collecting online data with SCTM (Smart crawling & Text mining), a data collecting and processing program. The data analysis period was from May 4th, 2017 to May 4th, 2018, meanwhile “restaurants, Seoul”, “restaurants, Busan” as keywords were utilized to collect the relevant data, eventually, in total 2.20 mb, approximately 68,700 words were collected. As a result of the data analysis, keywords such as restraurants, new, food, hotels, service, showed the high frequency while the results of centrality (Freeman’s degree centrality and Eigenvector centrality) indicated the similar rank with the frequency. At last, while some words were different with distinct rank between frequency and centrality. The CONCOR analysis was conducted for “restaurants, Seoul” there are 5 clusters were created as “food diversity”, “hospitality”, “social connection”, “consumer resource” and “restaurant location”. As for “restaurants, Busan” there are 4 clusters were created with the same names except “restaurant location”. Since the restaurant industry of Seoul was greatly developed, this study provides social network-oriented suggestions for restaurant industry of Busan.

목차

ABSTRACT
1. INTRODUCTION
2. LITERATURE REVIEW
3. METHODOLOGY
4. RESULTS
5. DISCUSSION AND CONCLUSIONS
REFERENCES

참고문헌 (31)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2018-594-003593339