• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.113-119
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• 2020

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

• Journal of Distribution Science
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• v.12 no.9
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• pp.53-63
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• 2014

Purpose - The rapid spread of SNS and increase of SNS users have heralded great changes in the tourism industry. Therefore, this study focused on how SNS characteristics- usefulness, convenience, interactivity, and intimacy - influence diffusivity, reliability and, consequently, user's preference for tourist attractions. Research design, data, and methodology - This study is designed not only to collect data with a questionnaire survey but also to test hypotheses with SEM by SPSS 18.0 and AMOS 18.0. Results - Usefulness, interactivity, and intimacy positively affect diffusivity, whereas convenience does not positively affect diffusivity. In addition, intimacy has a negative influence on reliability. However, diffusivity and reliability have positive impacts on the preference for tourist places. Conclusions - Certain characteristics of SNS facilitates the spreading of SNS tourist information. Usability and interactivity have positive impacts on the reliance of tourist information. Better communication can enhance the reliance of travel information. The influence of spreading tourist information has a positive influence on its reliance. Extension and reliance can have positive effects on the preference for tourist attractions.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.189-199
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• 2000

This Present study examines the Japanese Tourist basic law, its background as well as the formation process. Furthermore, this article also investigates the contents of the tourist basic law. In addition, I intend to accomplish a comparative study between a tourist policy enacted by the tourist policy council in 1995 years and the policy enacted in the 1960ㆍ70s. As the purpose of the study is concerned, the question related to a recomposition of contents of the Japanese tourist basic law in the 21st century is considered.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.637-644
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• 2017

This paper is based on the information left on SNS by the experienced tourist and, First, the tourist gathers various tourist information from SNS through Smart Tourism as suggested, Second, providing scheduling information for future tourist and the future tourist can modify and apply the information from experienced tourist. Third, the goal of this study is to design virtual tourism service based on above services where future tourist can post and modify tourism scheduling. Therefore, it is to obtain the effect of providing reliable tourism service to maximize the satisfaction of the tour through matching process between experience experiences and experience schedule.

• Archives of design research
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• v.13 no.1
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• pp.247-256
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• 2000

Recently, foreign tourists and car owners or motorists are increasing, so tourist sign boards are necessary to inform them. Unfortunately, tourist sign boards are difficult to understand because they are often written incorrectly. This paper has a thorough grasp of this problem and will present an ideal standard model which is precise and detailed. This paper includes research of tourist boards sign Seoul, Kyongju, Pusan, Kwangju, Yosu, Kwang reung in Korea. Also tourist sign boards in the U.K, France, Switzerland, Italy and Austria will be discussed. A survey was conducted of eight hundred people to determine tourist information is obtained. In conclusion, tourist sign board should convey accurate and useful information to people of all ages. Tourist information should be systematic and logical. An ideal standard model of tourist signs will render traveling easier for tourists all over the world. It will be more convenient for both kinds of tourist; domestic and foreign. Futhermore good tourist sign board will give an excellent and bright image.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1108-1121
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• 2019

As the quality and level of life rise, many people are doing search for various pieces of information about tourism. In addition, users prefer the search methods reflecting individual opinions such as SNS and blogs to the official websites of tourist destination. Many of previous studies focused on a recommendation system for tourist courses based on the GPS information and past travel records of users, but such a system was not capable of recommending the latest tourist trends. This study thus set out to collect and analyze the latest SNS data to recommend tourist destination of high interest among users. It also aimed to propose an altered TSP algorithm to recommend the optimal routes to the recommended destination within an area and a system to recommend the optimal tourist courses by applying the Elasticsearch engine. The altered TSP algorithm proposed in the study used the location information of users instead of Dijkstra's algorithm technique used in previous studies to select a certain tourist destination and allowed users to check the recommended courses for the entire tourist destination within an area, thus offering more diverse tourist destination recommendations than previous studies.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.203-214
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• 2012

As users of mobile devices such as smart phone are rapidly growing owing to the development of information technology, interest for information retrieval and a variety of services using mobile devices is gradually increasing. Users want to get the tourist information service through the use of mobile devices and accordingly, Korea local governments are trying to provide a variety of services on the mobile tourist information via smart phone. As more interest and requirements on mobile tourist information service, researches on types and preferences of mobile tourist information, measurement of the quality of service, the user's satisfaction and re-use is currently being done. However, meanwhile, the research on the content analysis classified and investigated a wide variety of numerical rating scale such as research topics of research papers, research methodology is wholly lacking. Thus, in terms of the research need on a systematic study of the domestic mobile tourist information, this study presented the research tendencies and implications of yearly research trends, research subjects, statistical analysis techniques, research methods, research models and theories related to the mobile tourist information focusing on journals listed on the National Research Foundation of Korea.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.9-18
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• 2018

Recently, the necessity and interest to improve the tourism preparedness for enhancing the quality of foreign tourists is increasing, but the related research is insufficient. The purpose of this study is to identify the preferential improvement elements related to the tourism preparedness of foreign tourists. To do this, we applied the R-IPA analysis to analyze and compare the elements affecting the tourist preparedness according to tourist type and time period. As a result of R-IPA analysis for all tourists, the elements that need to maintain the current quality levels were food, security, transit, shopping, and tourist attractiveness and the elements that need to be improved but low priority were language communication, travel expenses, and tourist information service. As a result of R-IPA analysis by tourist type, for individual tourists it is necessary to maintain current quality levels of transit, food, shopping, tourist attractiveness, and security. For group tourists, it is necessary to maintain current quality levels of accommodation, shopping, tourist attractiveness, and tourist information service, but food needs to be urgent improvement.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.61-68
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• 2021

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.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.255-262
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• 2020

Recently, medical tourism is recognized as a high value-added industry because of its longer period of stay and higher expenditure than general tourism. In particular, although the number of medical tourists visiting Korea is increasing, the perception of Korean medical services is low. The purpose of this paper is to develop the app which, based on medical tourism type, recommends tourism destinations. Additionally, this proposed app can expand general tourism as well. It can provide tourists with medical information easily by sorting types tourists. Besides, as medical tourists normally stay long, we can take the advantage of post-treatment time. This app collects medical information data and tourist destination data, and categorizes the types of medical tourists into four categories: disease medical tourism, traditional medical tourism, cosmetic medical tourism, and recreational medical tourism. It provides medical information according to each type and recommends customized tourist destinations. User-based collaborative filtering is applied for tourist destination recommendations.