• International Journal of Advanced Culture Technology
• /
• v.5 no.2
• /
• pp.82-89
• /
• 2017

The range of problems that can be handled by the activation of big data and the development of hardware has been rapidly expanded and machine learning such as deep learning has become a very versatile technology. In this paper, mnist data set is used as experimental data, and the Cross Entropy function is used as a loss model for evaluating the efficiency of machine learning, and the value of the loss function in the steepest descent method is We applied the GradientDescentOptimize algorithm to minimize and updated weight and bias via backpropagation. In this way we analyze optimal reliability value corresponding to the number of exercises and optimal reliability value without overfitting. And comparing the overfitting time according to the number of data changes based on the number of training times, when the training frequency was 1110 times, we obtained the result of 92%, which is the optimal reliability value without overfitting.

• International Journal of Advanced Culture Technology
• /
• v.7 no.4
• /
• pp.283-288
• /
• 2019

Neural networks have been reborn as a Deep Learning thanks to big data, improved processor, and some modification of training methods. Neural networks used to initialize weights in a stupid way, and to choose wrong type activation functions of non-linearity. Weight initialization contributes as a significant factor on the final quality of a network as well as its convergence rate. This paper discusses different approaches to weight initialization. MNIST dataset is used for experiments for comparing their results to find out the best technique that can be employed to achieve higher accuracy in relatively lower duration.

• Korean Management Science Review
• /
• v.31 no.4
• /
• pp.107-116
• /
• 2014

Recently, various types of information and communication technology (ICT) such as cloud computing, big data, and virtual reality have been progressed in the world. Also, it is expected that there are many domestic and foreign visitors in Gangwon-do due to the Pyeongchang winter olympic games in 2018. In this environment, it is necessary to improve the competitiveness of Gangwon-do in winter sports areas exploiting both existing IT infrastructure and application technologies. In this paper, for sustainable development of Gangwon-do winter sports IT industry after the Olympics, we propose efficient implementation methods of 3 winter sports IT convergence services and Gangwon-do ICT activation strategy. The proposed 3 winter sports IT service areas are as follows. 1) Realistic winter sports IT service, 2) Winter sports medical IT service 3) Winter sports record analysis IT service.

• The Journal of Information Systems
• /
• v.32 no.3
• /
• pp.117-132
• /
• 2023

Purpose The purpose of this study is to analyze the impact of policy changes in Busan's local currency, Dong Baek Jeon, on the use of Dong Baek Jeon. In particular, this study tried to investigate consumption changes due to changes in local currency policy depending on the region, industry, and consumer characteristics. Design/methodology/approach This study used the transaction data of Dong Baek Jeon franchise for analysis. Specifically, the data from January 2022 to December 2022 were used to analyze the current status of the use of Dong Baek Jeon and changes in consumption before and after policy changes. Findings As a result of the analysis, the consumption of Dong Baek Jeon tended to be concentrated in specific regions, industries, and ages. In most regions and ages, the top consumption industries were similar. The use of Dong Baek Jeon showed a clear change in the pattern of use depending on policy changes. Specifically, when the benefits were revised downward, the use of Dong Baek Jeon decreased, and when it was revised upward, it increased. Depending on the policy change, the rate of increase and decrease by region and consumer characteristics was relatively similar, but it was confirmed that there was a difference in the rate of increase and decrease depending on the industry.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.10a
• /
• pp.633-636
• /
• 2019

최근 글로벌화를 지향하는 국내 스타트업 중에 사업기획 단계에서부터, 법인설립, 현지마케팅 등을 해외에서 시작하는 해외창업 스타트업이 늘고 있다. 또한 4차 산업혁명의 진전에 따라 각종 IoT·센서 등에서 발생하는 대량의 데이터가 데이터 기반 산업·경제활성화를 견인하는 원동력으로 작용할 전망이다. 해외창업은 언어 장벽, 이질적 문화와 제도 등으로 성공하기 어려움에도 불구하고, 성공사례들이 종종 파악되고 있다. 따라서, 이런 사례가 파악되고 있는 미국, 인도, 일본, 싱가포르 등 4개국에서의 해외창업 성공사례들을 질적 분석을 통해 성공요인을 도출하고 해외창업 활성화 전략을 제시하였다.

• Journal of Intelligence and Information Systems
• /
• v.23 no.3
• /
• pp.69-94
• /
• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.18 no.4
• /
• pp.97-110
• /
• 2022

The purpose of this study is to analyze the level of public data convergence capabilities of administrative organizations and to explore important variables in data-based organizational capabilities. The theoretical background was summarized on public data and use activation, joint use, convergence, administrative organization, and convergence constraints. These contents were explained Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. The research model was set as the data-based organizational capabilities effect by a data-based administrative capability, public data operation capabilities, and public data operation constraints. It was also set whether there is a capabilities difference data-based on an organizational operation by the level of data convergence capabilities. This study analysis was conducted with hierarchical cluster analysis and multiple regression analysis. As the research result, First, hierarchical cluster analysis was classified into three groups. It was classified into a group that uses only public data and structured data, a group that uses public data on both structured and unstructured data, and a group that uses both public and private data. Second, the critical variables of data-based organizational operation capabilities were found in the data-based administrative planning and administrative technology, the supervisory organizations and technical systems by public data convergence, and the data sharing and market transaction constraints. Finally, the essential independent variables on data-based organizational competencies differ by group. This study contributed. As a theoretical implication, this research is updated on management information systems by explaining the Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. As a practical implication, the activity reinforcement of public data should be promoting the establishment of data standardization and search convenience and elimination of the lukewarm attitudes and Selfishness behavior for data sharing.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.149-169
• /
• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• Journal of Sport and Applied Science
• /
• v.4 no.3
• /
• pp.1-10
• /
• 2020

Purpose: This study is to explore which genre of sports culture contents will show the most consistent growth in the future and analyse the development outlook based on those results. Research design, data, and methodology: Case study was used for this research as it seemed to be the most appropriate approach in order to obtain the most complete and meaningful information from a particular phenomenon. A total of 15 participants were chosen to participate in a semi-structured in-depth interview and the recordings were typed out as text. In order to ensure validity and credibility of findings, peer and member check were conducted. Results: As a result, the sports culture content that is most likely to consistently grow in the future is games. Additionally, it is expected that sports culture contents will develop as new categories of sports culture contents emerge, as the evolution of sports culture content occurs through the combination with technology, as well as the activation of sensual sports contents, and the production of sports culture contents utilizing big data. Conclusions: It is concluded that convergence of sport, cultural contents, and technology will promptly progress, and it will promote the development of sport culture contents and related industry.

• Journal of Preventive Medicine and Public Health
• /
• v.56 no.3
• /
• pp.205-211
• /
• 2023

Cancer management has become a major policy goal for the government of the Korea. As such, the government introduced the National Cancer Control Plan (NCCP) to reduce the individual and social burdens caused by cancer and to promote national health. During the past 25 years, 3 phases of the NCCP have been completed. During this time, the NCCP has changed significantly in all aspects of cancer control from prevention to survival. The targets for cancer control are increasing, and although some blind spots remain, new demands are emerging. The government initiated the fourth NCCP in March 2021, with the vision of "A Healthy Country with No Concerns about Cancer Anywhere at Any Time," which aims to build and disseminate high-quality cancer data, reduce preventable cancer cases, and reduce gaps in cancer control. Its main strategies include (1) activation of cancer big data, (2) advancement of cancer prevention and screening, (3) improvement in cancer treatment and response, and (4) establishment of a foundation for balanced cancer control. The fourth NCCP has many positive expectations, similar to the last 3 plans; however, cross-domain support and participation are required to achieve positive results in cancer control. Notably, cancer remains the leading cause of death despite decades of management efforts and should continue to be managed carefully from a national perspective.