• Title/Summary/Keyword: Big data Era

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A Study on the Construction of a Car Camping Map and Recommendation of Car Camping based on SNS Text Mining Analysis for the Post-Corona Era (SNS 텍스트 마이닝 기반 포스트 코로나 신트렌드 차박 여행 지도 제작 및 차박지 추천에 관한 연구)

  • Kim, Minjeong;Kim, Soohyun;Oh, Jihye;Eom, Jiyoon;Kang, Juyoung
    • Journal of Information Technology Services
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    • v.20 no.5
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    • pp.11-28
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    • 2021
  • As untact travel has become a new trend in leisure culture due to the spread of COVID-19, car camping market is rapidly increasing. The sales of car camping-related goods increased by up to 600 percent, and the sales of SUV in Korea also increased by about four times. Despite the growth of the car camping market, there is a lack of research on the actual condition of the car camping market or research on the user's perspective. Therefore, in this study, a survey of actual camping users was conducted to derive factors that they consider important in camping, and through this, a car camping map was produced. As a result, two types of maps were produced: a map about the car camping site and convenience facilities closest to the car camping site in Gangwon-do, and a hash tag themed map based on keywords for each car camping site. We gathered data on portal sites and social media to obtain information related to camping sites and proceeded with analysis using text mining. In addition, we extracted keywords using network analysis techniques and selected key themes that represent them. This allows the user to choose a car camping site by selecting keywords that suit their taste. We hope that this research will help car camping researchers as a prior study and provide a foundation for leading a clean camping culture through clean camping campaign. Also, we hope that car camping users will be able to do quality trip.

A Scientific Quantitative Analysis on Vegetables of Joseon Dynasty using the Joseonwangjoshilrok based Data (조선왕조실록 과학계량적 분석을 통한 채소류의 통시적 고찰)

  • Kim, Mi-Hye
    • Journal of the Korean Society of Food Culture
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    • v.36 no.2
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    • pp.143-157
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    • 2021
  • This study aimed to analyze the periodic prevalence of the vegetables during the Joseon era with JoseonWangjoSilrok as a reference. The JoseonWangjoSilrok articles were collected from the Guksapyeonchanwewonhwe site, using web-crawling techniques to extract the relevant information. Out of 384,582 search results, 9,560 articles with vegetable-related keywords were found. According to the annual average vegetable recordings during the regimes of various kings, there were two peaking curves in the 15th and 18th centuryJoseon. The found was: 2,750 in the 18th century, 2,529 in the 15th century, 1,424 in the 16th century, and 1,018 in the 19th century. A Variable Interest Index was designed to ascertain the interestin vegetables of the 27 Joseon kings. The king most interested in vegetables was the 19th king Sookjong. The second most interested king was Youngjo. There were 5,105 vegetable-related findings within the JoseonWangjoSilrok related to specific species and categories of vegetables. Among the words found: 1,194 were stem-leaves vegetables (23.39%), 1,017 were root vegetables (19.92%), 1,148 were flower-fruit vegetables (22.49%), 1,144 were spice vegetables (22.41%), 95 were mushrooms (1.86%), and 507 were seaweeds (9.93%). Statistical analysis using ANOVA revealed the chronological factors that affected the vegetables' prevalence index.

Effect of the Organization's Autonomous Working Environment and Trust among Members on Workers' Job Immersion (조직의 자율적 근로환경과 구성원 간 신뢰가 근로자의 직무몰입에 미치는 영향)

  • Eun-Soo Han;Jong-Hyeon Hwang;Dong-Hyung Lee
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.2
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    • pp.13-21
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    • 2023
  • In the recent era of the fourth industrial revolution, many industries aim to maximize the efficiency of products and services by introducing cutting-edge technologies such as artificial intelligence and big data. In this situation, organizational culture is changing a lot due to the influx of the MZ generation with strong individualistic tendencies and the decreased face-to-face communication between members. However, active communication with colleagues is still essential to maximize performance, and the margins created by simplifying work processes and automating processes must be used for creating work performance. This requires cooperation and commitment through the job immersion of members who have an active attitude. This study analyzed how the organization's autonomous work environment and trust among members, which are creative work performance conditions, affect job immersion using raw data from the Occupational Safety and Health Research Institute. As a result, it was found that both the organization's autonomous working environment and trust among members significantly effected the members' job immersion. in order to achieve productivity and value improvement in companies, efforts are needed to increase workers' job immersion by building an autonomous working environment and trust among members. The results of this study are expected to contribute significantly to the search for ways to increase workers' job commitment to improve organizational productivity.

An Analysis of the Public Data for Making the Ambient Intelligent Service (공간지능화서비스 구현을 위한 공공데이터 분석)

  • Kim, Mi-Yun;Seo, Dong-Jo
    • Journal of Digital Convergence
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    • v.12 no.12
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    • pp.313-321
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    • 2014
  • In current society, the digital era that makes enormous amount of data, and the diversified city, the smart space, which has characteristics of creating, collecting and representing data, is appeared. After 2012, in the social media environment called hyper-connected society with wide-spread smart phone, people started to get interested in public data and big data by generalized mobile device and SNS. At first, development of forming platform of data was focused, but now, many different idea from diverse area have been suggested about data analysis and usage to visualize the space intellectualization service. To focus on the visualization process to increase the usage of this public data for ordinary people more than specialized people, this research grasps the present condition of open data and public data service from the current public data portal and considers the applicability of them. As the result of research, the analysis and application of data to ordinary people decrease the use of paper documents, and this research will help to develop the application which is fast and accurate about individual behavior and demand to utilize public data service in intellectual space.

Analysis of the Precedence of Stock Price Variables Using Cultural Content Big Data (문화콘텐츠 빅데이터를 이용한 주가 변수 선행성 분석)

  • Ryu, Jae Pil;Lee, Ji Young;Jeong, Jeong Young
    • The Journal of the Korea Contents Association
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    • v.22 no.4
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    • pp.222-230
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    • 2022
  • Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.

A Case Study on the Introduction and Use of Artificial Intelligence in the Financial Sector (금융권 인공지능 도입 및 활용 사례 연구)

  • Byung-Jun Kim;Sou-Bin Yun;Mi-Ok Kim;Sam-Hyun Chun
    • Industry Promotion Research
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    • v.8 no.2
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    • pp.21-27
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    • 2023
  • This study studies the policies and use cases of the government and the financial sector for artificial intelligence, and the future policy tasks of the financial sector. want to derive According to Gartner, noteworthy technologies leading the financial industry in 2022 include 'generative AI', 'autonomous system', 'Privacy Enhanced Computation (PEC) was selected. The financial sector is developing new technologies such as artificial intelligence, big data, and blockchain. Developments are spurring innovation in the financial sector. Data loss due to the spread of telecommuting after the corona pandemic As interests in sharing and personal information protection increase, companies are expected to change in new digital technologies. Global financial companies also utilize new digital technology to develop products or manage and operate existing businesses. I n order to promote process innovation, I T expenses are being expanded. The financial sector utilizes new digital technology to prevent money laundering, improve work efficiency, and strengthen personal information protection. are applying In the era of Big Blur, where the boundaries between industries are disappearing, the competitive edge in the challenge of new entrants In order to preoccupy the market, financial institutions must actively utilize new technologies in their work.

A Study on the Economic Effects of Big Tech Companies: Focusing on the Google Revenue and Tax Issues (글로벌 플랫폼이 국내 경제에 미치는 영향 연구: 구글 매출 추정 및 세원잠식 사례연구를 중심으로)

  • Kang, Hyoung-Goo;Jeon, Seongmin
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.1
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    • pp.1-11
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    • 2023
  • Big tech companies are further strengthening its status against the background of data accumulation, price competitiveness by the platform, and competitive advantage due to the network effect. The competition subcommittee of the European Union(EU) imposed a huge fine on Google for antitrust violations, which was interpreted as an attempt to collect Google's unpaid taxes. In fact, taxation efforts in the form of 'Google tax' are underway, targeting expedient tax avoidance by global platforms. It has power and has a considerable influence on the startup ecosystem. The domestic sales and tax scale of global platforms, which have a great impact on domestic content startups and small and medium-sized venture companies, are not accurately measured. In the case of Google, according to research literature, sales in Korea were estimated at about 2 trillion to 3 trillion won in 2017, but Google Korea reported sales of 290 billion won in 2021 and paid 13 billion won in taxes. This study aims to verify the economic effect of the global platform that has a great influence on Korea, and specifically to quantitatively estimate the annual domestic sales and taxes of Google, a representative global platform. As a result of estimating Google's annual domestic sales and taxes based on the figures presented in the document related to Google's economic effect published by Google, the result was 4 to 9 trillion won in annual sales and 390.6 to 913.1 billion won in taxes. This study is meaningful in that it provides basic data on the direction of national and tax policies in the future digital economy era by estimating the problem of tax authority by country of global platform companies with a specific example of Google.

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Analysis of media trends related to spent nuclear fuel treatment technology using text mining techniques (텍스트마이닝 기법을 활용한 사용후핵연료 건식처리기술 관련 언론 동향 분석)

  • Jeong, Ji-Song;Kim, Ho-Dong
    • Journal of Intelligence and Information Systems
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    • v.27 no.2
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    • pp.33-54
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    • 2021
  • With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

Achievements of Characterized Education for Healthcare Data Science Initiative (대학 특성화 사업 성과에 관한 연구-보건의료 데이터 사이언티스트 프로그램을 중심으로)

  • Park, HwaGyoo
    • Journal of Service Research and Studies
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    • v.9 no.3
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    • pp.87-99
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    • 2019
  • Healthcare and data science are often linked through finances as the industry attempts to reduce its expenses with the help of large amounts of data. Data science and medicine are rapidly developing, and it is important that they advance together. Data science is a driving force in transition of healthcare systems from treatment-oriented to preventive care in healthcare 3.0 era. It enables customized precision-based medicine that current healthcare systems cannot facilitate, and discovers more cost-effective treatment. Currently, healthcare big data is in the reality of medical institution, public health, medical academia, pharmaceutical sector as well as insurance agency. With this motivation, the medical college of Soonchunhyang university has performed a 'healthcare data science initiative(HDSI)' since 2014. Most of domestic HDSI programs focus on short-term contents such as mentoring and sharing cases for data science. Therefore, it is difficult to provide education tailored to the level of skills and job competency required at the practical site. Soonchunhyang HDSI implemented specialized strategies for improving resilience and response to changes in the IT education of current healthcare with the emphasis on the need for systematic activation of the practical HDSI. The HDSI has been performed as a part of on industry-academic link program in CK-1. Through quantitative and qualitative analysis, this paper discussed the HDSI process, performance, achievement, and implications.

Application Development for Text Mining: KoALA (텍스트 마이닝 통합 애플리케이션 개발: KoALA)

  • Byeong-Jin Jeon;Yoon-Jin Choi;Hee-Woong Kim
    • Information Systems Review
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    • v.21 no.2
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    • pp.117-137
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    • 2019
  • In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.