• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.161-166
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• 2021

The macroeconomic concept represents the movement of a country's economy, and it affects the overall economic activities of business, government, and households. In the macroeconomy, by looking at changes in national income, inflation, unemployment, currency, interest rates, and raw materials, it is possible to understand the effects of economic actors' actions and interactions on the prices of products and services. The US Federal Reserve System (FED) is leading the world economy by offering various stimulus measures to overcome the corona economic recession. Although the stock price continued to decline on March 20, 2020 due to the current economic recession caused by the corona, the US S&P 500 index began rebounding after March 23 and to 3,694.62 as of December 15 due to quantitative easing, a powerful stimulus for the FED. Therefore, the FED's economic stimulus measures based on macroeconomic indicators are more influencing, rather than judging the stock price forecast from the corporate financial statements. Therefore, this study was conducted to reduce losses in stock investment and establish sound investment by analyzing the FED's economic stimulus measures and its effect on stock prices.

• Knowledge Management Research
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• v.23 no.1
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• pp.187-201
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• 2022

Online reviews written by tourists provide important information for the management and operation of the tourism industry. The star rating of online reviews is a simple quantitative evaluation of a product or service, but it is difficult to reflect the sincere attitude of tourists. There is also an issue; the star rating and review content are not matched. In this study, a star rating prediction model based on online review content was proposed to solve the discrepancy problem. We compared the differences in star ratings and sentiment by continent through sentiment analysis on tourist attractions and hotels written by foreign tourists who visited Korea. Variables were selected through TF-IDF vectorization and sentiment analysis results. Logit, artificial neural network, and SVM(Support Vector Machine) were used for the classification model, and artificial neural network and SVR(Support Vector regression) were applied for the rating prediction model. The online review rating prediction model proposed in this study could solve inconsistency problems and also could be applied even if when there is no star rating.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.45-55
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• 2022

This study explores the issues of "eco-friendly consumption" through online media posts, and aims to identify changes in it. Total 6,812 blog posts on Naver, that included the words "eco-friendly consumption" and "eco-friendly lifestyle," published between 2005 and 2020, in five-year intervals, were analyzed. The results illustrated that consumption issues began with the identification of the causes of environmental problems however, "eco-friendly consumption" gradually gained importance, until it developed into preparing standards and alternatives for proper "eco-friendly consumption." In 2020, "eco-friendly consumption" values and ideal consumption practices were expanded into social movements. However, there is relatively little discussion on controlled and modest spending. Therefore, for the future direction of "eco-friendly consumption," it is necessary to thoroughly examine and highlight the agenda of controlled and modest living from a higher perspective.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.29-45
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• 2022

This study aims to analyze how the public perceive the climate change in South Korea. The climate change has been highlighted due to its social and environmental impact on future society during decades. In recent, the outbreak of COVID-19 alerted the causal relationship between diseases and the climate change and forced decision-makers to cope with possible future epidemics. Along with the social and political importance of the climate change, the perception and actions of the public also become significant. Thus, this study analyzes the trends in the public perception of climate change before and after the COVID-19, using social media big data from March 1, 2019 through February 28, 2022. The results show that the negative perception dominated the public's perception, but a little positive perception implies that numerous policies on the climate change may help the public convert their negative perception to the positive. This study may help the decision-makers develop future policies and strategies on the climate change and carbon neutrality by considering the demand-side perception, such as South Korean perception.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.291-303
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• 2021

The study tried to examine the characteristics of transcription culture on YouTube through narrative analysis methods. The study found five meaningful features in YouTube's transcription culture. YouTube's transcription culture was first characterized by efficient writing and learning skills. Second, there was a characteristic of a transcription to read and understand text more deeply. Third, it had the characteristics of five strategies to advance my writing. Fourth, YouTubers had time to self-heal and comfort through transcription. Fifth, YouTube's transcription culture has expanded and developed into left-handed writing and digital writing. The characteristics of these YouTubers' transcription culture are expected to enrich the transcription culture that has been handed down for many years.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.351-357
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• 2021

At the time when interest in the use of big data is rising in the face of the technological paradigm shift of the 4th industrial revolution, interest in the use of patented big data is increasing, especially as the proportion of intangible assets of companies increases. In addition to quantitative information, patent data contains various information such as unstructured text such as title, abstract, claim, citation and citation relations, drawings, and technology classification. It is judged that the use of treatment is important. Therefore, in this study, in order to systematically operate the innovative patent strategy framework and to secure a competitive advantage by strengthening the fundamental technological competitiveness of the company, we propose a method of using patent big data centering on the case of Company A, and verify its validity. I would like to suggest some implications. Through this, it is intended to raise awareness of the use of patent big data, and to suggest ways to use patent big data in connection with the company's company-wide strategy, business strategy, and functional strategy.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.131-142
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• 2023

In this paper, we propose a new station selection algorithm to solve the illegal parking problem of shared electric scooters and improve the service quality. Recently, as a solution to the urban transportation problem, shared electric scooters are attracting attention as the first and last mile means between public transportation and final destinations. As a result, the shared electric scooter market grew rapidly, problems caused by electric scooters are becoming serious. Therefore, in this study, text data are collected to understand the nature of the problem, and the problems related to shared scooters are viewed from the perspective of pedestrians and users in 'LDA Topic Modeling', and a station extension algorithm is based on this. Some parking lots have already been installed, but the existing parking lot location is different from the actual area of tow. Therefore, in this study, we propose an algorithm that can install stations at high actual tow density using mixed clustering technology using K-means after primary clustering by DBSCAN, reflecting the 'current state of electric scooter tow in Seoul'.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.501-508
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• 2022

The flow of global digitalization is leading to the emergence of a decentralized system environment based on blockchain or distributed ledger technology in the fields of economy, identity authentication, and logistics. Accordingly, a requirement that public services be searchable from several decentralized maritime service registries (MSRs) has been derived in terms of the discoverability of e-navigation services. This study describes a decentralized MSR environment composed of the MSR ledger and multiple local MSRs, and it has implemented a service search system that can search global e-navigation services in the environment through a web browser. This system is a decentralized application that dynamically generates service attributes, geometry information, and free text queries, and that provides users with relevant MSR and service access information from search results that are registered in the MSR ledger. In this study, we tested the established decentralized MSR environment and the system that performs service search within that environment, and we discussed its advantages and limitations.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.333-353
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• 2022

This study analyzed the relevance of the curriculum by applying topic modeling to book reports written as content area reading activities in the 'physics' class. In order to carry out the research, 332 physics book reports were collected to analyze the relevance among keywords and topics were extracted using STM. The result of the analysis showed that the main keywords of the physics book reports were 'thought', 'content', 'explain', 'theory', 'person', 'understanding'. To examine the influence and connection relationship of the derived keywords, the study presented degree centrality, between centrality, and eigenvetor centrality. As a result of the topic modeling analysis, eleven topics related to the physics curriculum were extracted, and the curriculum linkage could be drawn in three subjects (Physics I, Physics II, Science History), and six areas (force and motion, modern physics, wave, heat and energy, Western science history, and What is science). The analyzed results can be used as evidence for a more systematic implementation of content area reading activities which reflect the subject characteristics in the future.