• 디지털산업정보학회논문지
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• 제12권4호
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• pp.51-58
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• 2016

In the area of hotel and tourism sector, various research are analyzed using big data. Big data is being generated by any digital devices around us all the times. All the digital process and social media exchange produces the big data. In this paper, we analyzed the de-identification method of big data to use the personal information of hotel guests. Through the analysis of these big data, hotel can provide differentiated and diverse services to hotel guests and can improve the service and support the marketing of hotels. If the hotel wants to use the information of the guest, the private data should be de-identified. There are several de-identification methods of personal information such as pseudonymisation, aggregation, data reduction, data suppression and data masking. Using the comparison of these methods, the pseudonymisation is discriminated to the suitable methods for the analysis of information for the hotel guest. Also, among the pseudonymisation methods, the t-closeness was analyzed to the secure and efficient method for the de-identification of personal information in hotel.

• 디지털산업정보학회논문지
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• 제13권2호
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• pp.77-85
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• 2017

Due to the expansion of accommodation space caused by increase of population along with lifestyle changes, most of people spend their time indoor except for the travel time. Because of this, environmental change of indoor is very important, and it affects people's health and economy in resources. But, most of people don't acknowledge the importance of indoor environment. Thus, monitoring system for sustaining and managing indoor environment systematically is needed, and big data clusters should be used in order to save and manage numerous sensor data collected from many spaces. In this paper, we design a big data cluster for the indoor environment monitoring in order to store the sensor data and monitor unit of the huge building Implementation design big data cluster-based system for the analysis, and a distributed file system and building a Hadoop, HBase for big data processing. Also, various sensor data is saved for collection, and effective indoor environment management and health enhancement through monitoring is expected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2704-2719
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• 2022

Lately, neo-Chinese style furniture has been frequently noticed by product design professionals for the big part it played in promoting traditional Chinese culture. This article is an attempt to use big data semantic analysis method to provide effective design research method for neo-Chinese furniture design. By using big data mining program TEXTOM for big data collection and analysis, the data obtained from typical websites in a set time period will be sorted and analyzed. On the basis of "neo-Chinese furniture" samples, key data will be compared, classification analysis of overall data, and horizontal analysis of typical data will be performed by the methods of word frequency analysis, connection centrality analysis, and TF-IDF analysis. And we tried to summarize according to the related views and theories of the design. The research results show that the results of data analysis are close to the relevant definitions of design. The core high-frequency vocabulary obtained under data analysis, such as popular, furniture, modern, etc., can provide a reasonable and effective focus of attention for the designs. The result obtained through the systematic sorting and summary of the data can be a reliable guidance in the direction of our design. This research attempted to introduce related big data mining semantic analysis methods into the product design industry, to supply scientific and objective data and channels for studies on design, and to provide a case on the practical application of big data analysis in the industry.

• 한국응용과학기술학회지
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• 제37권1호
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• pp.76-82
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• 2020

Big data analysis in healthcare research seems to be a necessary strategy for the convergence of sports science and technology in the era of the Fourth Industrial Revolution. The purpose of this study is to provide the basic review to secure the diversity of big data and healthcare convergence by discussing the concept, analysis method, and application examples of big data and by exploring the application. Text mining, data mining, opinion mining, process mining, cluster analysis, and social network analysis is currently used. Identifying high-risk factor for a certain condition, determining specific health determinants for diseases, monitoring bio signals, predicting diseases, providing training and treatments, and analyzing healthcare measurements would be possible via big data analysis. As a further work, the big data characteristics provide very appropriate basis to use promising software platforms for development of applications that can handle big data in healthcare and even more in sports science.

• 디지털융복합연구
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• 제11권10호
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• pp.445-451
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• 2013

최근 국내 주요 금융권 및 방송사를 타깃으로 사이버 테러가 발생하여 많은 수의 PC가 감염되어 정상적인 서비스 제공이 어려워졌으며 이로 인한 금전적 피해도 매우 큰 것으로 보고되었다. 빅 데이터의 중요성 인식과 이를 마케팅에 이용하려는 노력은 매우 활발한데 비해 빅 데이터의 보안 및 개인정보보호에 대한 노력은 상대적으로 낮은 수준을 보이고 있다. 이에 본 연구에서는 빅 데이터 산업의 실태분석과 지능화되고 있는 빅 데이터 보안 위협과 방어 기술의 변화에 대해 알아보고, 빅 데이터 보안에 대한 향후 대응방안을 제시한다.

• 스마트미디어저널
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• 제4권3호
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• pp.56-61
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• 2015

빅데이터와 관련하여 많은 성공사례들이 보고되었지만 실제로 시스템을 구축하는 데 있어서는 여전히 많은 어려움이 있다. 기술적인 측면에서 데이터의 수집과 저장, 처리와 분석, 그리고 표현과 사용에 이르는 전 과정을 포괄적으로 이해해야 하고, 비즈니스적 측면에서는 구축된 시스템으로부터 얻을 수 있는 가치를 미리 파악하여 투자를 감행해야 하는 경영진에게 설명해야 한다. 본 연구는 빅데이터 정보시스템을 구축하는 것과 관련된 사항들을 쉽게 파악할 수 있는 5W 1H 프레임워크를 제공하고, 제시된 프레임워크를 기존의 빅데이터 사례들에 적용한 예시를 보여주었다. 투자를 위한 경영진의 의사결정을 이끌어내고 빅데이터 프로젝트의 종합적인 이해와 관리에 도움을 줄 수 있을 것으로 기대된다.

• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.475-487
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• 2020

The paper aims to facilitate a discussion around how big data technologies and data from citizens can be used to help public administration, society, and policy-making to improve community's lives. This paper discusses opportunities and challenges of big data strategies for government, society, and policy-making. It employs the presentation of numerous practical examples from different parts of the world, where public-service delivery has seen transformation and where initiatives have been taken forward that have revolutionized the way governments at different levels engage with the citizens, and how governments and civil society have adopted evidence-driven policy-making through innovative and efficient use of big data analytics. The examples include the governments of the United States, China, the United Kingdom, and India, and different levels of government agencies in the public services of fraud detection, financial market analysis, healthcare and public health, government oversight, education, crime fighting, environmental protection, energy exploration, agriculture, weather forecasting, and ecosystem management. The examples also include smart cities in Korea, China, Japan, India, Canada, Singapore, the United Kingdom, and the European Union. This paper makes some recommendations about how big data strategies transform the government and public services to become more citizen-centric, responsive, accountable and transparent.

• The Journal of Asian Finance, Economics and Business
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• 제10권2호
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• pp.109-121
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• 2023

This study aims to address the literature gap by examining the direct relationship between big data analytics capability, marketing innovation, and organizational innovations. Additionally, this study would examine big data analytics capability as the antecedent for both innovation types and how these relationships influence firm performance. The research model is developed based on the integration of resource-based view and knowledge-based view theories. The quantitative method is used as the research methodology for this study. Based on a purposive sampling method, a total of 115 questionnaires were obtained from managers in star-rated hotels located in Malaysia. Partial least square structural equation modeling (PLS-SEM) is utilized for the data analysis. The result shows that big data analytics capability positively affects marketing and organizational innovations. The findings show that big data analytics capability and organizational innovation positively influence firm performance. Nonetheless, the result revealed that marketing innovation is not positively related to firm performance. The findings also indicate to hotel managers the importance of big data analytic capability and the resources required to build and develop this capability. The contributions from this study enrich the literature on big data and innovation, which is particularly limited in the hospitality and tourism context.

• Journal of Information Technology Applications and Management
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• 제29권3호
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• pp.57-74
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• 2022

Recently, big data services have been used in various fields. In this situation, this research studied the intention to provide personal information from users, which is necessary to provide useful big data services. A survey was conducted on college students and ordinary people who have understood big data services. And path analysis was performed through Amos' structural equation. As a result of the study, it was found that privacy risks, trust in service providers, individual innovativeness, service incentives, social influence, and service design are major variables influencing the intention to provide personal information. And it was found that trust in service providers plays a mediating role in influencing the intention to provide personal information. In addition, big data services were classified into types for information acquisition and types related to purchase. Accordingly, it was further analyzed whether major variables differ in the path affecting the intention to provide personal information, and new implications were found. Companies that actually develop and provide big data services should establish different strategies by reflecting research results depending on the type of big data service provided.

• 식품보건융합연구
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• 제10권1호
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• pp.1-6
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• 2024

Purpose: The research aims to address the intricacies of AI and Big Data application within the food industry. This study explores the strategic implementation of AI and Big Data in the food industry. The study seeks to understand how these technologies can be employed to bolster consumer engagement and contribute to market expansion, while considering ethical implications. Research Method: This research employs a comprehensive approach, analyzing current trends, case studies, and existing academic literature. It focuses on the application of AI and Big Data in areas such as supply chain management, consumer behavior analysis, and personalized marketing strategies. Results: The study finds that AI and Big Data significantly enhance market analytics, consumer personalization, and market trend prediction. It highlights the potential of these technologies in creating more efficient supply chains, improving consumer satisfaction through personalization, and providing valuable market insights. Conclusion and Implications: The paper offers actionable insights and recommendations for the effective implementation of AI and Big Data strategies in the food industry. It emphasizes the need for ethical considerations, particularly in data privacy and the transparency of AI algorithms. The study also explores future trends, suggesting that AI and Big Data will continue to revolutionize the industry, emphasizing sustainability, efficiency, and consumer-centric practices.