• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.68-75
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• 2019

This study aims to look at the application methods of landscape architecture in response to the 4th Industrial Revolution. The results of the analysis of trends in the 4th Industrial Revolution and the subsequent search for application methods to the field of landscape architecture are as follows. First, the 4th Industrial Revolution means innovative change based on digital technology and seeks to create value based on intelligent information technology, and continuous growth is being made through innovation. This requires expertise to collect large amounts of information and creatively rework it, and a strategy to flexibly cope with changes in the times. Second, the status of technological use in response to the 4th Industrial Revolution in the field of landscape architecture is generalizing the establishment of precise analysis results such as survey technology and global mapping using drones, three-dimensional design simulation, and VR. In the field of traditional landscape architecture, efforts are made to obtain accurate fact-finding data on landscape site components. Third, the application methods in the field of landscape science according to the 4th Industrial Revolution in the future are required to supply precision technology and supply programs in the technology sector, and to provide a shared platform. In addition, a systemically standardized process will need to be established for this. In addition, educational efforts should be continued to professional manpower training and provide economic support for the development of technologies.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.33-42
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• 2021

As smartphone-based tourism platforms have become active, policy establishment and service enhancement using review data are being made in various fields. In the case of the preceding studies using tourism review data, most of the studies centered on domestic tourists were conducted, and in the case of foreign tourist studies, studies were conducted only on data collected in some languages and text mining techniques. In this study, 3,515 review data written by foreigners were collected by designating the "Daegu attractions" keyword through the online review site. And LDA-based topic modeling was performed to derive tourism topics. The spatial approach through global and local spatial autocorrelation analysis for each topic can be said to be different from previous studies. As a result of the analysis, it was confirmed that there is a global spatial autocorrelation, and that tourist destinations mainly visited by foreigners are concentrated locally. In addition, hot spots have been drawn around Jung-gu in most of the topics. Based on the analysis results, it is expected to be used as a basic research for spatial analysis based on local government foreign tourism policy establishment and topic modeling. And The limitations of this study were also presented.

• Knowledge Management Research
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• v.21 no.4
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• pp.129-156
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• 2020

The sharing economy is recognized as a new economic system based on the digital service platform, but the sharing economy has yet to be established in Korea due to a lack of social awareness and understanding. There is a need to enhance understanding and awareness of the sharing economy in positive perspective in order to make up business with advanced economies global and explore new markets. In this study, after collecting papers of the sharing economy over the past decade published by each academic field around the world, we reviewed them from academic lens and conducted a comprehensive analysis using meta analysis methodology. Then, we selected papers of MIS field and analyzed the trends of the MIS field research in these papers. As a result we identified the research trend of the sharing economy and the MIS research and drew the necessity of interdisciplinary research between the two studies by examining importance and relevance of MIS research in the sharing economy research. Therefore, we expect that this study contributes to promote interdisciplinary research with neighboring disciplines and to establish a positive social, economical and industrial position in Korea.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.20-31
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• 2021

The spread of non-face-to-face culture due to COVID-19 led to innovation in untact services and the increase of non-face-to-face communication through video conference platforms. However, it is difficult to identify nonverbal expressions in synchronous online communication. Moreover, it is hard to interact with people by making eye contact. Despite the positive effects of eye contact, including such as sharing emotions and helping build intimacy, no research has empirically verified the effectiveness of eye contact in synchronous online communication. Thus, the study verified the effectiveness of eye contact in synchronous online communication. Depending on the context of the communication and whether(or not) there is eye contact, six video treatments were used to measure four dependent variables-Continuance Intention to Use, Performance Expectancy, Interactivity, and Personal Connection. The study shows that the communication with eye contact in all contexts was rated higher than the one without eye contact in all measurement variables. This study will help to provide a better user experience in synchronous online communication by verifying the effectiveness of eye contact in synchronous online communication and proposing the need of technology and the direction of the technological development.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.173-184
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• 2022

Focusing on the TikTok, this paper studies the factors that influence the use intention, flow and addiction of the elderly in short videos from three aspects of media attraction, perceived usefulness and user characteristics through quantitative research methods. In recent years, influenced by various factors, more and more seniors have begun to indulge in short form videos, which will do harm to their physical and mental health. Therefore, the researchers believe it is necessary to identify the behavioral intention of seniors and the path to addiction. According to the research results, the attractiveness of TikTok and the characteristics of seniors have a positive impact on the usefulness of media. In addition, the study confirms that media usefulness has an impact on use intention and use behavior, which may develop into immersion and addiction. This study not only supplements the classical TAM theory, but also provides a reference for helping seniors to use the Internet in a healthy way. The researchers look forward to expanding the research on the various Internet platforms used by seniors in different countries and regions.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.149-162
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• 2020

This paper applied components of experience-based communication in terms of experience theory of Burnd H. Schmitt and context-based communication in the messenger platform environment through the scenario-based survey method, in order to study the influence of individual experiences, shared experiences, ubiquitous connectivity, and contextual usefulness on the perceived value and use intention of chatbot. Through this, the study is to provide companies in various service industries with practical approaches to further promote the use of chatbot. The implications of this study are as follows. First, as most chatbots still do not exceed the human planning level of designing them, it is necessary to consider how to design individual experience elements functionally according to the customer's intention to speak when developing the chatbot. Second, the chatbot should be designed not only from the perspective of completing specific tasks at any real time in anywhere, but also from the overall perspective of enhancing the quality of interaction, including the situation to which the customer belongs. Third, since the chatbot is likely to be anthropomorphized by users, it is important to be cautious about determining the chatbot's 'persona' and 'tone and manner' when developing the chatbot. Customer satisfaction is the most important criterion for the success of chatbot development. In other words, the quality of planning and data rather than the quality of artificial intelligence algorithms determines the utilization of chatbot. This is why companies are trying to make interactions with chatbot as close as possible to human interactions.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.15-29
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• 2021

Many countries and companies are pursuing and developing Artificial intelligence as it is the core technology of the 4th industrial revolution. Global IT companies such as Apple, Microsoft, Amazon, Google and Samsung have all released their own AI assistant hardware products, hoping to increase customer loyalty and capture market share. Competition within the industry for AI agent is intense. AI assistant products that command the biggest market shares and customer loyalty have a higher chance of becoming the industry standard. This study analyzed the current status of major overseas and domestic IT companies in the field of artificial intelligence, and suggested future strategic directions for voice UI technology development and user satisfaction. In terms of B2B technology, it is recommended that IT companies use cloud computing to store big data, innovative artificial intelligence technologies and natural language technologies. Offering voice recognition technologies on the cloud enables smaller companies to take advantage of such technologies at considerably less expense. Companies also consider using GPT-3(Generative Pre-trained Transformer 3) an open source artificial intelligence language processing software that can generate very natural human-like interactions and high levels of user satisfaction. There is a need to increase usefulness and usability to enhance user satisfaction. This study has practical and theoretical implications for industry and academia.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.319-325
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• 2021

With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.23-36
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• 2022

Objectives : This study aimed to provide basic data on intervention strategies that occupational therapists can access by systematically analyzing the intervention and effectiveness for youth with disabilities. Methods : The RISS, PubMed, and Web of Science databases were used to search for papers published between 2006 and 2021. The keywords were "Disability AND Adolescents OR Young adult AND Transition education OR Transition program". Seven papers were selected for analysis, and the full text was reviewed. The keywords and national relations were analyzed and visualized using the WoS (Web of Science) and VOSviewer programs. Results : The participants were classified into five types (ASD or ADHD, ID, DD, and physical disability). The areas used for the intervention were mixed into three categories: occupation (academic), self-management (time), and interaction (personal relations and communication). Sociality and adaptation, quality of life, and at least one of the three categories of daily life activities showed significant improvement. Conclusions : This study can be used as basic data to expand the area where only OTs can contribute while grasping the research trend of the conversion program and presenting the direction of exchange with various experts by organizing the application and its effects.

• 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.