• Information Systems Review
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• v.21 no.1
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• pp.39-59
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• 2019

E-learning has improved the educational effect by making it possible to learn anytime and anywhere by escaping the traditional infusion education. As the use of e-learning system increases with the increasing popularity of e-learning, it has become important to measure e-learning satisfaction. In this study, we used the mixed research method to identify satisfaction factors of e-learning. The mixed research method is to perform both qualitative research and quantitative research at the same time. As a quantitative research, we collected reviews in Udemy.com by text mining. Then we classified high and low rated lectures and applied topic modeling technique to derive factors from reviews. Also, this study conducted an in-depth 1:1 interview on e-learning learners as a qualitative research. By combining these results, we were able to derive factors of e-learning satisfaction and dissatisfaction. Based on these factors, we suggested ways to improve e-learning satisfaction. In contrast to the fact that survey-based research was mainly conducted in the past, this study collects actual data by text mining. The academic significance of this study is that the results of the topic modeling are combined with the factor based on the information system success model.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.289-306
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• 2005

As FRBR defines structural framework based on ER modeling for bibliographic data elements, an effective tool is required to implement FRBR model. In this paper, we present the implementation of FRBR model based on Topic Maps. To show the effectiveness of Topic Maps as the implantation language of FRBR, we implement FRBR model of MyongSungHwangHu by means of Topic Maps. We can ascertain that topic-association of Topic Maps conceptually harmonize with entity-relation of FRBR, which means that Topic Maps is suitable for the implementation of FRBR model.

• Journal of Korea Port Economic Association
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• v.36 no.3
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• pp.39-54
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• 2020

In the presidential political system, the word of the president has great influence on the formation of national policy and the decision-making process. Policy priorities are determined according to the president's ideology and core values, and various policies are established and executed according to the priorities. Therefore, this paper analyzes the contents of the president's speech. Since the president's speech is a semantic datum, in order to analyze unstructured text, big data analysis is conducted through the methods of machine learning and deep learning. In this study, the president's speech at the "National Sea Day" commemoration was obtained 1996 onwards and analyzed using topic modeling. As a result of the analysis, all the presidents' speeches were delivered with a view of the ocean that was consistent with the direction of their administration. It was confirmed that the ocean-industry-resource topics, which are the intrinsic values of the ocean, were not damaged and consistently emphasized by all presidents.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.430-440
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• 2021

We analyzed research trends of 288 Korean academic dissertations and articles regarding platform work, using topic modeling and keyword network analysis method. Research disciplines of many studies were laws, business administration, and economics fields. Thigh frequent themes were platform labor protection measures and direct or indirect effects of the sharing economy. The main keywords were digital, value, industry, and labor in terms of infrastructure and structural change. Besides, the main topics were the protection of platform workers, the values of sharing services, digital paradigm, and platform regulations. Based on the results of the analysis, we derived four implications and suggestions such as researching structural frames in macroscopic contexts, generalizing case analysis, and technology supplementation by applying average and quantitative analysis methods, researching individual competency development to realize the essential symbiotic value of sustainability, and developing customized vocational education and training programs.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.145-153
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• 2020

In the rapidly changing era of the fourth industry, big data is being used in various fields. In recent years, the use of big data has been rapidly applied to overall cultural and artistic contents, and among them, the use of big data is essential as a film genre with a lot of capital. This research method is analyzed as the film , which won the Palme d'Or Prize of the 72nd Cannes Film Festival in 2019 and the works and directors' award at the Academy Awards. The analyzed value predicts the film's performance through opinion mining, which gives the value of the change and sensitivity of each data cycle, and extracts the utilization index and topic keywords of SNS such as Facebook and Twitter to reflect the audience's interest. Identify the factors. As such, if model performance and model development can be predicted through model analysis of film performance using big data, the efficiency of the film production process will be maximized while the risk of production cost and the risk of film failure will be minimized.

• Informatization Policy
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• v.29 no.4
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• pp.43-66
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• 2022

With the development of artificial intelligence technology, competition for artificial intelligence technology patents around the world is intensifying. During the period 2000 ~ 2021, artificial intelligence technology patent applications at the US Patent and Trademark Office have been steadily increasing, and the growth rate has been steeper since the 2010s. As a result of analyzing Korea's artificial intelligence technology competitiveness through patent indices, it is evaluated that patent activity, impact, and marketability are superior in areas such as auditory intelligence and visual intelligence. However, compared to other countries, overall Korea's artificial intelligence technology patents are good in terms of activity and marketability, but somewhat inferior in technological impact. While noise canceling and voice recognition have recently decreased as topics for artificial intelligence, growth is expected in areas such as model learning optimization, smart sensors, and autonomous driving. In the case of Korea, efforts are required as there is a slight lack of patent applications in areas such as fraud detection/security and medical vision learning.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.347-356
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• 2023

In the recent war between Ukraine and Russia, low-orbit satellite communication played a major role, and Korea laid a foothold for low-orbit satellite communication services with the successful launch of Nuri in May 2023 and entered a full-scale civilian space age competition. In order to create an ecosystem for ICT digital transformation and data convergence in the field of low-orbit satellite communication, this paper conducts user sentiment analysis by importing posts from Reddit, one of the world's SNS, and extracts need-related sentences through need mining to identify user needs, performs topic modeling to classify topics, and prepares an action plan according to these topics. We hope that this study will be used as a policy resource for the development and innovation of new business models in the field of low-orbit satellite communication, bridging the digital information gap and solving social problems, contributing to sustainable digital transformation and enhancing soft power.

• Smart Media Journal
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• v.13 no.2
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• pp.95-107
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• 2024

The development of environmentally friendly products and services has become a trend, and the development and utilization of eco-friendly textiles with economic value is gaining attention as a new business model. Analyzing and identifying trends and developments in eco-friendly textiles can provide important information and insights for various stakeholders such as companies, governments, and consumers to help them achieve sustainable growth. For this study, we collected and analyzed data from newspaper articles mainly covering the textile and fashion sector from 2000 to June 2023. A total of 12,331 articles containing the keyword 'eco-friendly textiles' were collected, and after performing morphological analysis on the extracted data, Latent Dirichlet Allocation and Dynamic Topic Modeling analysis were performed to identify topics by year. The results of the study are expected to provide strategic guidance and insights for the sustainable development of the textile industry, thereby helping to promote the research, development, and commercialization of eco-friendly textiles.

• Proceedings of the Korean Information Science Society Conference
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• 2010.11a
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• pp.74-75
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• 2010

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.176-178
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• 2018

트위터는 최대 140자의 단문을 주고받는 소셜 네트워크 서비스이다. 트위터의 해시 태그는 주로 문장의 핵심 단어나 주요 토픽 등을 링크하게 되는데 본 논문에서는 이러한 정보를 이용하여 키워드 추출에 활용한다. 문장을 Character CNN, Bi-LSTM을 통해 문장 표현을 얻어내고 각 Span에서 이러한 문장 표현을 활용하여 Span 표현을 생성한다. Span 표현을 이용하여 각 Span에 대한 Score를 얻고 높은 점수의 Span을 이용하여 키워드를 추출한다.