제주대학교 Repository

다차원 순위 모델 기반의 관광후기 분석

Metadata Downloads
Author(s)
유상욱
Issued Date
2017
URI
http://dcoll.jejunu.ac.kr/jsp/common/DcLoOrgPer.jsp?sItemId=000000008240
Abstract
With the development of ICT, the continuous spread of smart phones, and the increase of SNS users, a large amount of data is being generated in real time, and the kind and quantity thereof is rapidly. In particular, Review Data through smartphones and SNS are important big data that can be used to derive the actual consumption, purchase pattern, and preference. Although the research is proceeding with the use of Review Big Data in the tourism society, the research of Jeju tourism is mainly composed of the questionnaires based on the questionnaire and there is a limited amount of data to analyze the perception of tourists visiting Jeju, because it is a lack of data and structured format. In addition, various data mining techniques for analyzing Review Data have been studied, but it focused on efficiency-oriented technology improvement, and research on analytical models to derive more effective and valuable information by fusing existing technologies is limited. In this study, we propose a multidimensional ranking model that is applicable not only to Review data but also to analyze other types of data. The multidimensional ranking model enables ranking of the evaluation subject and the domain in various perspectives so that meaningful information can be derived. The multidimensional ranking model is of value in that it is a generalized model that can be applied to ranking data as well as Review data as well as other types of big data. In particular, this study analyed a 4,037 Jeju tourist Review data from 185 tourist sites that posted on Trip Advisor from 2015 to 2016 based on the multidimensional ranking model. We conducted a multidimensional ranking analysis of the rankings of tourist attractions, key keyword rankings, seasons, and years with high level of interest and favorability. As a result of the analysis, it received attention by tourists in the order of Seongsan ilchulbong, O'sulloc tea museum and Udo Island and be liked in the order of Hallasan National Park, Hamdeok Beach and Udo Island. The key keyword analysis of Jeju tourism has been used to refer to many keywords related to tourists and natural sightseeing places accompanied with children, and it has been analyzed that key words indicating the identity of each sightseeing spot are mainly mentioned through analysis of key keyword frequency by sightseeing spot. Through the keyword association analysis, the result of the analysis that leads to the analysis of the key keyword frequency of the previous tourist spots, and also, it was analyzed that tourists use coupons more frequently in order to receive discounts. Based on the results of the analysis, it was possible to derive the interest, liking, and perception of the tourist in the tourist attraction.
Alternative Title
Analysis of Tourism review based on Multi-dimensional Ranking Model
Affiliation
제주대학교 일반대학원
Department
대학원 관광융합소프트웨어학과
Advisor
김근형
Awarded Date
2017. 8
Table Of Contents
표 차례 iii
그림 차례 iv
ABSTRACT v
제1장 서론 1
제1절 연구배경 및 목적 1
1. 연구의 배경 1
2. 연구의 목적 2
제2절 연구의 방법 및 구성 3
1. 연구의 방법 3
2. 논문의 구성 3
제2장 이론적 배경 5
제1절 데이터 마이닝 5
1. 데이터 마이닝의 개념 5
2. 데이터 마이닝 추진 단계 5
3. 데이터 마이닝의 기법 7
1) 연관분석 7
2) 다차원분석(OLAP) 8
(1) OLAP의 특징 9
4. 데이터 마이닝 관련 기존 연구 고찰 9
제2절 제주 관광지에 대한 선행연구 11
제3장 연구설계 12
제1절 연구문제 12
제2절 분석 절차 13
제3절 분석 모델(다차원 순위 모델) 14
제4장 데이터 수집 및 분석 18
제1절 데이터 원천 18
제2절 데이터 수집 19
제3절 텍스트 전처리(Text Preprocessing) 20
제4절 분석 결과 22
1. 데이터 수집 결과 및 표본의 특성 22
2. 분석 결과 23
1) 제주에서 관심도가 높은 관광지 23
2) 제주에서 호감도가 높은 관광지 25
3) 제주 관광에서의 핵심 키워드 27
4) 관광지별 핵심 키워드 29
5) 키워드 연관성 분석 31
제5장 결론 34
제1절 연구 요약 및 시사점 34
제2절 연구의 한계 36
참고문헌 38
Degree
Master
Publisher
제주대학교 일반대학원
Citation
유상욱. (2017). 다차원 순위 모델 기반의 관광후기 분석
Type
Dissertation
Appears in Collections:
General Graduate School > Tourism Convergence Software
Authorize & License
  • AuthorizeOpen
Files in This Item:

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.