• Journal of Digital Convergence
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• v.18 no.9
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• pp.181-190
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• 2020

The purpose of this study is to analyze the trends of wearable keywords using text mining methodology. To this end, 11,952 newspaper articles were collected from 1992 to 2019, and frequency analysis and bi-gram analysis were applied. The frequency analysis showed that Samsung Electronics, LG Electronics, and Apple were extracted as the highest frequency words, and smart watches and smart bands continued to emerge as higher frequency in terms of devices. As a result of the analysis of the bi-gram, it was confirmed that the sequence of two adjacent words such as world-first and world-largest appeared continuously, and related new bi-gram words were derived whenever issues or events occurred. This trend of wearable keywords will be useful for understanding the wearable trend and future direction.

• Advanced Industrial SCIence
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• v.2 no.4
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• pp.36-43
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• 2023

Native plants thrive naturally in specific areas without human intervention, offering significant potential as genetic resources and biotechnological assets across multiple sectors. To harness this potential, our focus was on analyzing domestic patents related to native plants, investigating their uses, effectiveness, active components, and extraction methods. Using the Korea Forest Service's National Standard Plant List, we gathered data from 988 patents on native plants and 430 patents on the use of native plant seeds. This comprehensive patent analysis aimed to reveal research patterns, technology levels, and emerging trends. The goal is to identify research trends, current technology levels, and provide insights for future patent applications involving native plants.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.115-128
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• 2022

The purpose of this study is to conduct keyword trend analysis using articles data on the impact of Covid-19 in the aviation in dustry. In this study, related articles were extracted centering on the keyword "Airline" by dividing the period of 6months before and after Covid-19 occurrence. After that, Topic modeling(LDA) was performed. Through this, The main topic was extracted in the event of an epidemic such as Covid-19, It is expected to be used as primary data to predict the aviation industry's impact when occurrence like Covid-19.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.164-173
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• 2012

Recently, while sharing various values of an individual through fast information delivery with the consciousness change of consumers, the trend is now changing by needs of consumers from the trend that companies took the lead in the past. In addition, while jewelries are changed to fashion's consumer goods, it is time that the domestic jewelry industry also needs development of products applied with various colors and visual emotion that consumers demand. Accordingly, much interest in natural colorful gems and the consumption market are being increased in the jewelry industry. Accordingly, this research has progressed the necessity, the status analysis and consumer preference analysis of products development using Semiprecious Stone, and extracted the target market by style and needs of consumers through a consumer trend survey and image analysis survey for development of products. And, this research has set a design directionality by extracting adjectives that can be applied to design preference images by age. This study has confirmed the necessity and possibility of Semiprecious Stone products development based on the analysis of jewelry market.

• Journal of Energy Engineering
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• v.21 no.4
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• pp.325-338
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• 2012

Currently, there are the technologically urgent needs of fabricating the hyper coal (HC) based on the approach to extracting mainly effective organics from low rank coals (LRCs), because some industrial countries pursue global sustainability dealing with hot issues such as local energy supply security as well as global warming. In this study, as of the fabrication of clean HCs via LRCs upgrading, we comprehensively review the R&D status of two solvent extraction technologies, namely, Ohm heating (OH) and microwave irradiation (MI) extraction processes on the basis of the performance indicator such as a HC extraction yield.

• Archives of design research
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• v.20 no.3 s.71
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• pp.49-60
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• 2007

As the world is in the age of globalization and information, we observe diverse changes in the market environment. Since wide-spread internet services and global networks made ubiquitous learning and business possible, equalizing consumers' ideology and preference, new trend and life style could be introduced easily. This study stipulates on the theoretical concept of the wellbeing consumer and LOHAS consumer. Consumers of LOHAS could be sampled out through pre-questionnaire targeting at selected food, clothing, and shelter based on companies of both wellbeing and general brands. Through this it is attempted to measure wellbeing emotion, recognition quotient of emotion and reason, affirmation and negation, mental emotion quotient, and preference in order to find out their value and to ultimately come up with what web design should be aiming at. Conclusions are as follows: Firstly, consumers easily recognize emotional identification from the web pages of wellbeing brand, rather than that of general brands. Secondly, what web pages of wellbeing brand recognize is reason, not emotion. Thirdly, the design of wellbeing brands scored higher than those of general brands in terms of positive aspects such as hospitality and familiarity, and high mental emotion quotient could not affect the consumers' preference toward web design. Fourthly, wellbeing brands win more preference than general brands do, and preference becomes higher after customers' visit to web pages basically. Lastly, sampled emotional adjectives toward the web designs of wellbeing brands marked a aesthetic graph figure, without leaning toward an active or stable one. It is expected that this study can serve as a groundwork to create proper strategies to actively involve consumers in industrial sphere.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.167-173
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• 2020

This study aims to analyze the number and trend of news media news through timely analysis of how the articles about airlines and employees show changes before and after Corona19 in the situation where the world economy faces various problems due to the global pandemic of Corona19. For this purpose, the number of articles and trends related to airlines and employees were analyzed and visualized before and after Corona19 using the Korea Press Foundation Bigkinds news analysis service. For this purpose, the Bigkinds service system was extracted from January 1, 2019 to May 31, 2019 and from January 1, 2020 to May 31, 2020. The results of the analysis showed that the number of articles before and after Corona 19 exploded when aviation related events occurred. And it was confirmed that the trend is changing due to the restructuring news. Government and airlines will need to make active efforts to overcome the crisis in the aviation industry due to the impact of Corona 19. The results of this study are significant in that it analyzed the number and trends related to news articles before and after Corona 19, and suggested practical implications for establishing strategies for the future impacts on airlines and employees.

• Knowledge Management Research
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• v.23 no.4
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• pp.315-338
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• 2022

In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• The Journal of Bigdata
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• v.5 no.1
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• pp.29-39
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• 2020

Purpose The atmosphere of respect for individual tastes that have spread throughout society has changed the consumption trend. As a result, the travel industry is also seeing customized travel as a new trend that reflects consumers' personal tastes. In particular, there is a growing interest in 'film-induced tourism', one of the areas of travel industry. We hope to satisfy the individual's motivation for traveling while watching movies with customized travel proposals, which we expect to be a catalyst for the continued development of the 'film-induced tourism industry'. Design/methodology/approach In this study, we implemented a methodology through 'OCR' of extracting and suggesting film location information that viewers want to visit. First, we extract a scene from a movie selected by a user by using 'OpenCV', a real-time image processing library. In addition, we detected the location of characters in the scene image by using 'EAST model', a deep learning-based text area detection model. The detected images are preprocessed by using 'OpenCV built-in function' to increase recognition accuracy. Finally, after converting characters in images into recognizable text using 'Tesseract', an optical character recognition engine, the 'Google Map API' returns actual location information. Significance This research is significant in that it provides personalized tourism content using fourth industrial technology, in addition to existing film tourism. This could be used in the development of film-induced tourism packages with travel agencies in the future. It also implies the possibility of being used for inflow from abroad as well as to abroad.