• Title/Summary/Keyword: Big data Era

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Innovation and Challenges of Urban Creative Products in Digital Media Art - Tourist cities in China for example

  • Ma Xiaoyu;Lee Jaewoo
    • International Journal of Advanced Culture Technology
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    • v.12 no.1
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    • pp.175-181
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    • 2024
  • The paper examines the impact of digital media art on urban creative products, analyzing opportunities and challenges in the digital era. It emphasizes the development of urban cultural and creative products, highlighting their significance and future growth potential. The digital media era provides unprecedented innovation opportunities, utilizing advanced tools for efficient design, production, and marketing. Trends like personalization, customization, AI, and big data offer new expressions and market prospects. Cultural products evolve in design, marketing, and sales channels due to digital media, with tools like social media and e-commerce platforms opening new promotion avenues. Case studies illustrate digital media's role in driving innovation and enhancing user experiences. The paper addresses challenges in market competition, copyright, and technological renewal, while recognizing opportunities from AI and big data. The creative industries must adapt and innovate to remain relevant. Looking ahead, urban creative products will evolve under digitalization, relying on digital means to attract consumers and enhance brand value. Cultural products, beyond economic entities, disseminate urban culture and creative spirit. In the digital era, urban creative products demonstrate potential and necessity, prompting a reevaluation of digital technology's role. Through continuous innovation, this field contributes to cultural and economic levels, impacting urban characteristics and heritage. Urban creative products play an increasingly vital role in the global cultural and creative economy.

Marketing Performance and Big Data Use During the COVID-19 Pandemic: A Case Study of SMEs in Indonesia

  • WIBOWO, Sampurno;SURYANA, Yuyus;SARI, Diana;KALTUM, Umi
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.7
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    • pp.571-578
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    • 2021
  • The outbreak of the COVID-19 pandemic, which began in 2020, had a significant impact on the economy and business activities worldwide. Large companies, as well as small businesses were affected, many of them had to scale down or divert their businesses, and some even had to stop. This extraordinary situation requires business people to make innovations and adjustments to survive during a pandemic. Entering the digital era, business players are helped by the ease of internet access, which will make it easier for SME players to get data from their consumers. Business actors can use this data to innovate and create new creations to improve business performance during this pandemic. This research aims to identify how small and medium enterprises can take advantage of Big Data to improve marketing performance through innovation and value creation. The research methodology used the in this research is quantitative method. The respondents are SME producers of food and beverage, with a total of 150 respondents. The results in the study indicate that all the proposed hypotheses are accepted. The most significant influence is found on the relationship of Big Data to value creation. The lowest effect was obtained from the relationship between Big Data and marketing performance through the mediation variable and innovation capability.

A Study on the Classification of Unstructured Data through Morpheme Analysis

  • Kim, SungJin;Choi, NakJin;Lee, JunDong
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.4
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    • pp.105-112
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    • 2021
  • In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.

A Study on the Ferry Sewol Disaster Cause and Marine Disaster Prevention Informatization with Big Data : In terms of ICT Administrative Spatial Informatization and Maritime Disaster Prevention System development (세월호사고원인과 빅데이터 해양방재정보화연구 -ICT행정공간정보화와 해양방재시스템개발 측면에서-)

  • Lee, Sang-Yun;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.6
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    • pp.567-580
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    • 2016
  • In recent years, our society, because of the arrival of a new paradigm according to the rapid changes in ICT has entered into future smart society and the ubiquitous era. So it can be a notable turning point in the marine disaster prevention system with big data, aspects of the era change. Therefore, this study was to derive a desirable vision for the big data marine disaster prevention informatization in terms of ICT maritime disaster prevention system development as preparedness for the maritime disaster by applying 'scenario planning' as a foresight method. Soon this study derived a successful marine disaster prevention informatization strategy as preparedness for the maritime disaster like Ferry Sewol Disaster. It proposed the big data marine disaster prevention informatization system with the use of the administrative aspects of information with spatial informatization as big data information. Also this study explored the future leadership strategy of the big data marine disaster prevention informatization in smart society. Eventually in 2030 to around, In order to still remain our marine disaster prevention informatization as a leading ICT nation, this study suggested the following strategy. It is important to ready the advanced Big Data administrative spatial informatization system In terms of prevention of incidents like Ferry Sewol Disaster.

Activation of Health Care Big Data (헬스케어 분야에서의 빅데이터 활용 활성화 방안)

  • Moon, Ja-hwa
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.483-486
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    • 2021
  • With the explosive increase in data, the 'big data era' has arrived, focusing on deriving new values and insights through data. With the development of data analysis technology, the importance of data analysis and utilization in the field of diagnosis and treatment as well as prevention is expanding, while the use of big data is emerging in the healthcare field. Moreover, as the three data-related laws (Personal Information Protection Act, Information and Communication Network Act, and Credit Information Act) were passed in January 2020, it became possible to use a wide range of big data through pseudonym information. However, the use of healthcare big data is still struggling due to various policies and regulations, inconsistent data quality, and the absence of specialized personnel. Therefore, in this study, examines the current state of use of big data in the healthcare field, and analyzes the challenges, overseas cases, plans, and expected effects for activation of healthcare big data.

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Research on the introduction and use of Big Data for trade digital transformation (무역 디지털 트랜스포메이션을 위한 빅데이터 도입 및 활용에 관한 연구)

  • Joon-Mo Jung;Yoon-Say Jeong
    • Korea Trade Review
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    • v.47 no.3
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    • pp.57-73
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    • 2022
  • The process and change of convergence in the economy and industry with the development of digital technology and combining with new technologies is called Digital Transformation. Specifically, it refers to innovating existing businesses and services by utilizing information and communication technologies such as big data analysis, Internet of Things, cloud computing, and artificial intelligence. Digital transformation is changing the shape of business and has a wide impact on businesses and consumers in all industries. Among them, the big data and analytics market is emerging as one of the most important growth drivers of digital transformation. Integrating intelligent data into an existing business is one of the key tasks of digital transformation, and it is important to collect and monitor data and learn from the collected data in order to efficiently operate a data-based business. In developed countries overseas, research on new business models using various data accumulated at the level of government and private companies is being actively conducted. However, although the trade and import/export data collected in the domestic public sector is being accumulated in various types and ranges, the establishment of an analysis and utilization model is still in its infancy. Currently, we are living in an era of massive amounts of big data. We intend to discuss the value of trade big data possessed from the past to the present, and suggest a strategy to activate trade big data for trade digital transformation and a new direction for future trade big data research.

A Study on Improvement of Accounting Curriculum in Big Data Age (빅데이터시대의 회계교육과정 개선방안 연구)

  • Jeong, Eun-Han;Kim, Kyung-Ihl
    • Journal of Convergence for Information Technology
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    • v.8 no.5
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    • pp.145-152
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    • 2018
  • The paper aims to present the direction in which accounting education should proceed to enhance the expertise of accounting works in the new era in which big data is the center. This paper examines the definition and analysis of big data, and reviews the effectiveness through big data development in accounting expertise with specific references. Also, this paper presents some of the plans selected by professional accounting bodies and universities to address the topic of big data in the accounting curriculum. According to the plan, big data could provide a blueprint for the future role of accounting and financial experts. Therefore, what this study suggests is to improve educational content by adding big data topics to current accounting curricula in order to help accounting professionals of future generations prepare for technologies related to big data analysis in advance.

Cases of Stock Analysis through Artificial Intelligence Using Big Data (빅데이터를 활용한 인공지능을 통한 주식 예측 분석 사례)

  • Choi, Min-gi;Jo, Kwang-ik;Jeon, Min-gi;Choi, hun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.303-304
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    • 2021
  • In the 21st century, as we enter the Fourth Industrial Revolution, research in various fields utilizing big data is being conducted, and innovative and useful technologies are constantly emerging in the world. Among several technologies recently in the big data era, among various fields utilizing some algorithms of artificial intelligence, it shines in the field of finance and is used for pin tech, financial fraud detection and risk management, etc., and recently Even in the booming stock market, it is used for investment prediction and investment factor analysis using artificial intelligence algorithm models. In this paper, we plan to investigate various research cases and investigate trends in how they are used in the stock market through artificial intelligence that utilizes big data.

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A Study of Establishment of Medical CRM Model in the Post-Corona Era : Focusing on the Primary-Level Hospital (포스트 코로나시대 의료기관 CRM시스템 구축모형 : 의원급 의료기관을 중심으로)

  • Kim, Kang-hoon;Ko, Min-seok;Kim, Hoon
    • Journal of Information Technology Applications and Management
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    • v.28 no.1
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    • pp.1-12
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    • 2021
  • The purpose of this study is to analyze the medical ecosystem in the post-corona era. In addition, this study introduces a new medical CRM model that allows primary-level hospitals to overcome the economic difficulties and to occupy a competitive advantage in the post-corona era. The medical environment in the post-corona era is expected to be changed by non-face-to-face treatment, reinforcement of public medical care, the transformation of a medical system centered on the primary-level hospitals, and the use of AI and big data technologies. The medical CRM model presented in this study emphasizes the establishment of mutual customer relationships through close information exchange between patients, primary-level hospital, and the government. In the post-corona era, primary-level hospitals should not simply be approached as private hospital pursuing profitability. These should be reestablished as the hospitals that can provide public health care services while ensuring stable profitability.

Text Mining and Visualization of Unstructured Data Using Big Data Analytical Tool R (빅데이터 분석 도구 R을 이용한 비정형 데이터 텍스트 마이닝과 시각화)

  • Nam, Soo-Tai;Shin, Seong-Yoon;Jin, Chan-Yong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1199-1205
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    • 2021
  • In the era of big data, not only structured data well organized in databases, but also the Internet, social network services, it is very important to effectively analyze unstructured big data such as web documents, e-mails, and social data generated in real time in mobile environment. Big data analysis is the process of creating new value by discovering meaningful new correlations, patterns, and trends in big data stored in data storage. We intend to summarize and visualize the analysis results through frequency analysis of unstructured article data using R language, a big data analysis tool. The data used in this study was analyzed for total 104 papers in the Mon-May 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 1,538 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.