• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.171-189
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• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• Management & Information Systems Review
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• v.36 no.4
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• pp.129-148
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• 2017

Conventional exhibition management information systems recommend tourist attractions that are close to the place in which an exhibition is held. Some recommended attractions by the location-based recommendation could be meaningless when nothing is related to the exhibition's topic. Our goal is to recommend attractions that are related to the content presented in the exhibition, which can be coined as content-based recommendation. Even though human exhibition curators can do this, the quality is limited to their manual task and knowledge. We propose an automatic way of discovering attractions relevant to an exhibition of interests. Language resources are incorporated to discover attractions that are more meaningful. Because a typical single machine is unable to deal with such large-scale language resources efficiently, we implemented the algorithm on top of Apache Spark, which is a well-known distributed computing framework. As a user interface prototype, a web-based system is implemented that provides users with a list of relevant attractions when users are browsing exhibition information, available at http://bike.snu.ac.kr/WARP. We carried out a case study based on Korean Tourism Organization Linked Open Data with Korean Wikipedia as a language resource. Experimental results are demonstrated to show the efficiency and effectiveness of the proposed system. The effectiveness was evaluated against well-known exhibitions. It is expected that the proposed approach will contribute to the development of both exhibition and tourist industries by motivating exhibition visitors to become active tourists.

• Journal of Korean Society of Rural Planning
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• v.25 no.2
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• pp.15-21
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• 2019

The agricultural environment is changing and becoming more advanced due to the influence of the 4th Industrial Revolution. From the basic plan of Rural Informatics to the current level of 2nd generation smart farms aimed at improving productivity using Big data, cloud network and more IoT technology. We are continuing to provide support and research and development. However, many problems remain to be solved in order to supply and settle smart farms in Korea. The purpose of this study is to provide a method of collecting and sharing data on farming environment and to help improve the income and productivity of farmers based on collected data. In the case of hog farm, the multiple sensors for environmental data like temperature, humidity and gases and the network environment for connecting the internet were established. The environment sensor was made using the ESP8266 Node MCU board as micro-controller, DHT22 sensor for temperature and humidity, and MQ series sensors for various gases in the hog pens. The network sensor was applied experimentally for one month and the environmental data of the hog farm was stored on a web database. This study is expected to raise the importance of collecting and managing the agricultural and environmental data, for the next generation farmers to understand the smart farm more easily and to try it by themselves.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.231-244
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• 2022

With the improvement of people's living standards and the development of tourism, tourists have greater freedom in choosing destinations. Therefore, as an indicator of satisfaction with scenic spots, tourist comments are becoming increasingly prominent. This paper aims to compare and analyze the landscape image of the Five Great Mountains in China and provide specific strategies for its development. The online reviews of tourists on the Online Travel Agency (OTA) website about the Five Great Mountains from 2015 to 2018 are collected as research samples. The text analysis method and R language are used to analyze the content of the tourist reviews, while the high-frequency words in the word cloud are used for visual display. In addition, the entropy weight method is used to determine the index weight and tourist satisfaction is evaluated to understand the weaknesses of those scenic spots. The results of the study show that firstly, the tourist satisfaction with the Five Great Mountains is basically consistent with its popularity. Secondly, through weight analysis, tourists pay special attention to the landscape features and environmental health of the scenic area, so that relevant departments should focus on building the landscape characteristics and improving the environmental health of the scenic area. At the same time, the accommodation and service management of the scenic spot cannot be ignored. Finally, according to the analysis results, suggestions are made on how to improve the tourist satisfaction with the Five Great Mountains.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1075-1087
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• 2011

We analyze the tourist satisfaction of the Daegu City Tour which plays a big role in the local tourism boosting through '2011 Visit Daegu Year'. To analyze a causal relation among factors, we proposed a structural equation model consisting of four latent variables of the tour: motivation, expectation, satisfaction, and future behaviors. Using data from the actual tourists of the Daegu City Tour, we found out that tourists' motivation before the tour does not affect tourists' satisfaction after the tour. However those who have higher motivation have positive future behavior and those who have the higher expectation are more satisfied with the tour. Meanwhile, the expectation before the tour does not lead the future behavior but the satisfaction after the tour influences the positive future behavior.

• Korean Association of Arts Management
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• no.58
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• pp.89-119
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• 2021

This study empirically analyzes the factors that affect the people's enjoyment of pure culture and arts, especially art exhibitions. We use 56,588 sample data from the "The Survey of Cultural Enjoyment" collected by the Ministry of Cultrure, Sports and Tourism over the last 10 years and perform multiple regression and Multi-Way ANOVA to analyze the effect of individual's cultural experience on art exhibit visits. The results of the analysis show that the experience of participating in culture and arts events, culture and arts education, and participation in culture and arts clubs have a positive effect on the art exhibition visits. We also identify the positive interaction effects between the three independent variables. In other words, it was found that the average number of visits to art exhibitions was higher for groups who had experience of participating in culture and arts events, culture and arts education, and culture and arts clubs. This study provides a first empirical analysis on personal factors influencing art exhibition visits in Korea and lays the groundwork for future studies in developing a comprehensive predictive model for cultural art visits. In addition, we give policy implications and suggestions specifically, mid-term policies related to promoting art exhibition visits as an extension of individual's engagement with pure culture and arts through big data analysis.

• The Journal of Bigdata
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• v.6 no.1
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• pp.179-196
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• 2021

With the spread of untact culture resulting from the Covid-19 pandemic, the size of the car camping market has expanded to minimize contact with others. As a result, SUVs have exceeded sales of sedans, and sales of recreational vehicles (RVs) have increased by 101% compared to the same period last year. Despite the explosive increase in demand for car camping, research on car camping has not matched this increase. Therefore, in this study, we intended to conduct a study focused on car camping users. According to a survey of Naver's famous car camping cafe, it was difficult to find articles, maps, and websites with car camping places. Analysis of car camping websites showed that most only post information about the camping itself, so details of car camping places were not available. Furthermore, according to a survey derived from related prior studies and literature surveys, most users urged solutions to the problem of unauthorized garbage dumping in the car camping locations. In addition, car camping users wanted to receive information on amenities near the car camping places. Therefore, we aimed to establish a car camping website that provides basic information on car camping places and nearby convenience facilities. Moreover, to solve the problem of garbage dumping, we provided a category wherein users can post pictures of clean camping campaigns. We also developed a business model utilizing the certification process of clean camping. The business model is designed with a structure wherein car camping users are rewarded through the clean camping certification process. Compensation for clean camping certification was proposed to be provided through partnerships with domestic automakers, Korea Tourism Organization, and Small Business Market Promotion Agency.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.536-548
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• 2018

Public data has been transformed from provider-oriented information disclosure to a form of personalized information sharing centered on individual citizens since government 3.0. As a result, the government is implementing policies and projects to maximize the value of public data and increase reuse. This study analyzes the issues related to public data in the news and seeks the status of government agencies and government projects by issue. We conducted semantic analysis on domestic online news and public agency bidding information including public data and conducted the work of linking major key words derived with social and economic values inherent in public data. As a result, major issues related to public data were divided into broader access to public data, growth of new technology, cooperation and conflict among stakeholders, and utilization of the private sector, which were closely related to transparency, efficiency, participation, and innovation mechanisms. Also major agencies of four issues include the Ministry of Strategy and Finance and Seoul, Ministry of Culture, Sports and Tourism and Gyeonggi-do, Ministry of Trade, Industry and Energy and Incheon, and Ministry of Land, Infrastructure and Transport and Gyeongsangbuk-do. Most of the issues are being led by the government.

• Journal of Agricultural Extension & Community Development
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• v.13 no.1
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• pp.49-67
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• 2006

The purpose of this study was to suggest development strategies of a village of Hwaseong-si where several programs using it's traditional items have been operated since 2003 according to the policy of Rural Traditional Thema Village Development implemented by Rural Development Administration(RDA). The village is located in Yodang-ri, Yanggam-myun, hwaseong-si in Gyounggi province. The village is called as 'Eunheng Namu Maeul' which means 'ginkgo tree village' since the tree is almost 350 years old and beautifully huge. Including this big tree there are much more traditional items such as organic dairy farming, hand-made cheese, legends and traditional plays. Using this items and government subsidies, the village has managed various tour programs and other income increasing projects. This study analyzed the strengths, weaknesses, opportunities and threats of the current situation of the village with the related materials and data to find out development strategies for the village-based programs and projects. This study recommended the followings as a major result of this study. The huge ginkgo tree at the village could be a better traditional attractive item when paths and wood of ginkgo trees will be built up especially utilizing the original huge one around the village. Like this, the item of hand made cheese could be a much more valuable traditional item when there will be an advanced facility for the people's working together. The social actives of the village have been weakened because of few young dwellers living there, therefore there needs a special subsidizing project for the village to hire a young manager having some social skills and knowledges. The situation being urbanized in front of the village needs precisely checking and implementing the Hwaseong-si's urbanization policy so that the urbanization could be harmonized with the maintenance and development of the traditional items of the village.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.371-382
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• 2017

This study aims to analyze the research trend of cultural policy-related papers based on 832 key words among 186 whole articles in the Journal of Cultural Policy by the Korea Culture & Tourism Institute from October 2008 to January 2017. The analysis was performed using a big data analysis technique called the Semantic Network Analysis. The Semantic Network Analysis consists of frequency analysis, density analysis, centrality analysis including degree centrality, betweenness centrality, and eigenvector centrality. Lastly, the study shows a figure visualizing the results of the centrality analysis through Netdraw program. The most frequently exposed key words were 'culture', 'cultural policy/administration', 'cultural industry/cultural content', 'policy', 'creative industry', in the order. The key word 'culture' was ranked as the first in all the analysis of degree centrality, betweenness centrality and eigenvector centrality, followed by 'policy' and 'cultural policy/administraion'. The key word 'cultural industry/cultural content' with very high frequency recorded high points in degree centrality and eigenvector centrality, but showed relatively low points in betweenness centrality.