In-Seon Kim, Chi-Seo Jeong, Tae-Won Jung, Jin-Kyu Kang, Kye-Dong Jung
언어
영어(ENG)
URL
https://www.earticle.net/Article/A391037
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
영어
The development of the fourth industry has enabled users to quickly share a lot of data online. We can analyze big data on information about tourist attractions and users' experiences and opinions using artificial intelligence. It can also analyze the association between characteristics of users and types of tourism. This paper analyzes individual characteristics, recommends customized tourist sites and proposes a system to provide the sacred texts of recommended tourist sites as AR services. The system uses machine learning to analyze the relationship between personality type and tourism type preference. Based on this, it recommends tourist attractions according to the gender and personality types of users. When the user finishes selecting a tourist destination from the recommendation list, it visualizes the information of the selected tourist destination with AR.
목차
Abstract 1. Introduction 2. Related Works 2.1 AR 2.2 Big Data-Based Tourism Image Analysis 2.3 Analysis of Tourism Preference Using Machine Learning 3. Proposed System 3.1 System Architecture 3.2 Analysis of Character-Based Tourism Image Using Machine Learning 3.3 AR Framework Based on Emotional Map 4. Applying System 4.1 Analysis of Tourism Image Based on User Characteristics 4.2 Implemented System 5. Conclusion References
키워드
Image AnalysisARBig DataMachine LearningEmotional TourismRecommendation System
저자
In-Seon Kim [ Master Student, Graduate School of Smart Convergence, Kwangwoon University, Korea ]
Chi-Seo Jeong [ Master Student, Graduate School of Smart Convergence, Kwangwoon University, Korea ]
Tae-Won Jung [ Doctoral Student, Department of Realistic Convergence Contents Kwangwoon University Graduate School, Korea ]
Jin-Kyu Kang [ The Spatial Party, Digital-ro 26-gil, Guro-gu, Seoul 08393, Korea ]
Kye-Dong Jung [ Professor, Ingenium College of liberal arts, Kwangwoon University, Korea ]
Corresponding Author