• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.81-93
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• 2022

There are many natural hot springs and mineral springs as well as the cultural heritage of the three kingdoms period in the Geum River basin including Chungcheong region. No specific regeneration and publicity plans for deteriorated facilities in this area has been presented. This study aims to suggest promising hot spots and complex water culture belt in the Chungcheong region and Geum River basin through the spatial interpretation of resources. The northern part of the Geum River basin is expected to become a therapeutic spring belt with many hot springs and CO₂-rich springs. In the central and southern parts of the Geum River basin, it is considered that it will be possible to promote convergence publicity by using groundwater resources and cultural assets.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.59-75
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• 2019

This study was carried out to explore the 4th Industrial Revolution technology from the perspective of the landscape industry to provide the basic data necessary to increase the virtuous circle value. The 4th Industrial Revolution, the characteristics of the landscape industry and urban regeneration were considered and the methodology was established and studied including the technical classification system suitable for systematic research, which was selected as a framework. First, the 4th Industrial Revolution technology based on digital data was selected, which could be utilized to increase the value of the virtuous circle for the landscape industry. From 'Element Technology Level', and 'Core Technology' such as the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence, Robot, 'Peripheral Technology', Virtual or Augmented Reality, Drones, 3D 4D Printing, and 3D Scanning were highlighted as the 4th Industrial Revolution technology. It has been shown that it is possible to increase the value of the virtuous circle when applied at the 'Trend Level', in particular to the landscape industry. The 'System Level' was analyzed as a general-purpose technology, and based on the platform, the level of element technology(computers, and smart devices) was systematically interconnected, and illuminated with the 4th Industrial Revolution technology based on digital data. The application of the 'Trend Level' specific to the landscape industry has been shown to be an effective technology for increasing the virtuous circle values. It is possible to realize all synergistic effects and implementation of the proposed method at the trend level applying the element technology level. Smart gardens, smart parks, etc. have been analyzed to the level they should pursue. It was judged that Smart City, Smart Home, Smart Farm, and Precision Agriculture, Smart Tourism, and Smart Health Care could be highly linked through the collaboration among technologies in adjacent areas at the Trend Level. Additionally, various utilization measures of related technology applied at the Trend Level were highlighted in the process of urban regeneration, public service space creation, maintenance, and public service. In other words, with the realization of ubiquitous computing, Hyper-Connectivity, Hyper-Reality, Hyper-Intelligence, and Hyper-Convergence were proposed, reflecting the basic characteristics of digital technology in the landscape industry can be achieved. It was analyzed that the landscaping industry was effectively accommodating and coordinating with the needs of new characters, education and consulting, as well as existing tasks, even when participating in urban regeneration projects. In particular, it has been shown that the overall landscapig area is effective in increasing the virtuous circle value when it systems the related technology at the trend level by linking maintenance with strategic bridgehead. This is because the industrial structure is effective in distributing data and information produced from various channels. Subsequent research, such as demonstrating the fusion of the 4th Industrial Revolution technology based on the use of digital data in creation, maintenance, and service of actual landscape space is necessary.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.69-79
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• 2022

This study aims to assess the current understanding of the landscape of wind power facilities as renewable energy sources that supply sightseeing, tourism, and other opportunities. Therefore, social media data related to the landscape of wind power facilities experienced by visitors from different regions was analyzed. The analysis results showed that the common characteristics of the landscape of wind power facilities are based on the scale of wind power facilities, the distance between overlook points of wind power facilities, the visual openness of the wind power facilities from the overlook points, and the terrain where the wind power facilities are located. In addition, the preference for wind power facilities is higher in places where the shape of wind power facilities and the surrounding landscape can be clearly seen- flat ground or the sea are considered better landscapes. Negative keywords about the landscape appear on Gade Mountain in Taibai, Meifeng Mountain in Taibai, Taiqi Mountain, and Gyeongju Wind Power Generation Facilities on Gyeongshang Road in Gangwon. The keyword 'negation' occurs when looking at wind power facilities at close range. Because of the high angle of the view, viewers can feel overwhelmed seeing the size of the facility and the ridge simultaneously, feeling psychological pressure. On the contrary, positive landscape adjectives are obtained from wind power facilities on flat ground or the sea. Visitors think that the visual volume of the landscape is fully ensured on flat ground or the sea, and it is a symbolic element that can represent the site. This study analyzes landscape awareness based on the opinions of visitors who have experienced wind power facilities. However, wind power facilities are built in different areas. Therefore, landscape characteristics are different, and there are many variables, such as viewpoints and observers, so the research results are difficult to popularize and have limitations. In recent years, landscape damage due to the construction of wind power facilities has become a hot issue, and the domestic methods of landscape evaluation of wind power facilities are unsatisfactory. Therefore, when evaluating the landscape of wind power facilities, the scale of wind power facilities, the inherent natural characteristics of the area where wind power facilities are set up, and the distance between wind power facilities and overlook points are important elements to consider. In addition, wind power facilities are set in the natural environment, which needs to be protected. Therefore, from the landscape perspective, it is necessary to study the landscape of wind power facilities and the surrounding environment.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.48-57
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• 2013

Smartphones provide users with environment for communication and sharing information and at the same time play an important role of mobile technology and mobile art development. Smartphone technology-related researches are being accelerated especially with the advent of mobile Augmented Reality(AR) age, but the studies on user participation that is essential for AR content industry were insufficient. In that regard, the assistance from mobile art area that has already developed these characteristics is essential. Thus, this article is to classify mobile art that has not been studied a lot domestically into feature phone usage and smartphone usage and to analyze each example case with the three most used methods. The usage of feature phones which use the sound and images of mobile devices can be divided into three: installation and performing methods, single channel video art method and five senses communication method. On the other hand, the usage of smartphones that use sensors, cameras, GPS and AR can be divided into location-based AR, marker-based AR and markerless AR. Also, as a result of examining mobile AR content utilization technology by industries, combined methods are utilized; tourism and game-related industries use location-based AR, education and medicine-related industries use marker-based AR, and shopping-related industries use markerless AR. The development of AR content industry is expected to be accelerated with mobile art that makes use of combined technology method and constant communication method through active participation of users. The future development direction of mobile AR industry is predicted to have minimized HMD, integration of hologram technology and artificial intelligence and make the most of big data and social network so that we could overcome the technological limitation of AR.

• Journal of Korean Society of Rural Planning
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• v.30 no.2
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• pp.13-24
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• 2024

This study conducts an analysis of social media big data pertaining to island tourism resources, aiming to discern the diverse forms and categories of island tourism favored by consumers, ascertain predominant resources, and facilitate objective decision-making grounded in scientific methodologies. To achieve this objective, an examination of blog posts published on Naver from 2022 to 2023 was undertaken, utilizing keywords such as 'Island tourism', 'Island travel', and 'Island backpacking' as focal points for analysis. Text mining techniques were applied to sift through the data. Among the resources identified, the port emerged as a significant asset, serving as a pivotal conduit linking the island and mainland and holding substantial importance as a focal point and resource for tourist access to the island. Furthermore, an analysis of the disparity between existing island tourism resources and those acknowledged by tourists who actively engage with and appreciate island destinations led to the identification of 186 newly emerging resources. These nascent resources predominantly clustered within five regions: Incheon Metropolitan City, Tongyeong/Geoje City, Jeju Island, Ulleung-gun, and Shinan-gun. A scrutiny of these resources, categorized according to the tourism resource classification system, revealed a notable presence of new resources, chiefly in the domains of 'rural landscape', 'tourist resort/training facility', 'transportation facility', and 'natural resource'. Notably, many of these emerging resources were previously overlooked in official management targets or resource inventories pertaining to existing island tourism resources. Noteworthy examples include ports, beaches, and mountains, which, despite constituting a substantial proportion of the newly identified tourist resources, were not accorded prominence in spatial information datasets. This study holds significance in its ability to unearth novel tourism resources recognized by island tourism consumers through a gap analysis approach that juxtaposes the existing status of island tourism resource data with techniques utilizing social media big data. Furthermore, the methodology delineated in this research offers a valuable framework for domestic local governments to gauge local tourism demand and embark on initiatives for tourism development or regional revitalization.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.6
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• pp.16-24
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• 2020

The purpose of this study is to analyze the usage behavior of Seoullo 7017, the first public garden in Korea, to understand the usage status by analyzing blogs, and to present usage behavior and improvement plans for Seoullo 7017. From June 2017 to May 2020, after Seoullo 7017 was open to citizens, character data containing 'Seoullo 7017' in the title and contents of NAVER and·DAUM blogs were converted to text mining and socialization, a Big Data technique. The analysis was conducted using social network analysis. The summary of the research results is as follows. First of all, the ratio of men and women searching for Seoullo 7017 online is similar, and the regions that searched most are in the order of Seoul and Gyeonggi, and those in their 40s and 50s were the most interested. In other words, it can be seen that there is a lack of interest in regions other than Seoul and Gyeonggi and among those in their 10s, 20s, and 30s. The main behaviors of Seoullo 7017 are' night view' and 'walking', and the factors that affect culture and art are elements related to culture and art. If various programs and festivals are opened and actively promoted, the main behavior will be more varied. On the other hand, the main behavior that the users of Seoullo 7017 want is 'sit', which is a static behavior, but the physical conditions are not sufficient for the behavior to occur. Therefore, facilities that can cause sitting behavior, such as shades and benches must be improved to meet the needs of visitors. The peculiarity of the change in the behavior of Seoullo 7017 is that it is recognized as a good place to travel alone and a good place to walk alone as a public multi-use facility and group activities are restricted due to COVID-19. Accordingly, in a situation like the COVD-19 pandemic, more diverse behaviors can be derived in facilities where people can take a walk, etc., and the increase of various attractions and the satisfaction of users can be increased. Seoullo 7017, as Korea's first public pedestrian area, was created for urban regeneration and the efficient use of urban resources in areas beyond the meaning of public spaces and is a place with various values such as history, nature, welfare, culture, and tourism. However, as a result of the use behavior analysis, various behaviors did not occur in Seoullo 7017 as expected, and elements that hinder those major behaviors were derived. Based on these research results, it is necessary to understand the usage behavior of Seoullo 7017 and to establish a plan for spatial system and facility improvement, so that Seoullo 7017 can be an important place for urban residents and a driving force to revitalize the city.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.54-67
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• 2023

Mount Tai, with an elevation of 1,532 meters, has a reputation as ''The Most Revered of the Five Sacred Mountains (五嶽獨尊)", despite not being the highest mountain in China. A guidebook is a book or pamphlet that contains an introduction and description of specific activities or facilities, especially detailed and accurate information about scenic spots, which provide superior vistas to than other commercially publicized locations. The study aims to investigate Mount Tai's landscape characteristics by analyzing the landscape types and elements, the Kernel Density, the Mean Center and the Standard Deviational Ellipse of the landscape elements appearing in guidebooks introducing Mount Tai. The research results of this study are summarized as follows. First, the landscape type characteristics of Mount Tai are dominated by natural landscapes, which are different from what was shown highlighted in poems and Big Data as they proposed that the landscape characteristics of Mount Tai is dominated by human activities. Second, from the perspective of subdivided landscape types, the landscape elements that appeared in Mount Tai are topography, structure, architecture, plants, semantics, human beings and image orderly, based on the proportion of landscape elements. Third, from the perspective of landscape elements by times series, "Fengshan (封禅)", "sacrifices (祭祀)" and "legends" mostly appeared in the 1950s and 1980s, and after the 1990s, "climbing" and "overlooking" mostly appeared. Fourth, the landscape elements of Mount Tai are concentrated in Daiding (岱顶) and Dai Temple (岱庙) in all periods in terms of spatial distribution. This will become an important space for Mount Tai scenic spots in the future. Moreover, as a whole, the landscape elements of Mount Tai have changed from the concentrated distribution form in Mount Tai scenic spot to the scattered distribution form including Mount Tai and Tai'an City. This will provide necessary enlightenment for the landscape preservation and the re-production of guidebooks of Mount Tai scenic spot in the future.