• 융합정보논문지
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• 제8권1호
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• pp.179-185
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• 2018

빅데이터는 이제 더 이상 미래 혁신의 아이콘이 아니라 인류가 당면한 과제를 해결하기 위한 하나의 수단으로써 공고히 자리매김해 가고 있다. 빅데이터의 활용과 개인정보 보호는 분명 양면성을 갖고 있다. 데이터의 활용을 강조할 경우 개인이 공개를 원하지 않는 사생활은 필연적으로 침해 될 것이고, 개인정보 보호를 강조할 경우 어설픈 수준의 빅데이터 연구만 가능해 공공의 목적을 달성 하는데 어려움을 겪을 수 있다. 본 연구에서는 개인정보 침해의 문제점을 알아보고 빅데이터의 활용과 개인정보의 보호를 하기 위해서 취합하는 빅데이터를 익명화하는 방안을 제시하였다. 이를통해 빅데이터 활용 뿐만 아니라 개인정보 침해의 문제점을 해결할 수 있을 것으로 보인다.

• 한국의류학회지
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• 제42권1호
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• pp.148-158
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• 2018

This study analyzes recent trends in fashion retailing instigated by the fourth industrial revolution and approaches the trends in terms of the convergence of big data and artificial intelligence. The findings are as below. First, companies like 'Edited' and 'Stylumia' offer solutions that support the strategic decisions of fashion brands and fashion retailers by analyzing big data using artificial intelligence. Second, the convergence of big data and artificial intelligence scales personalized service on the web as examples of 'Coded Couture', 'StitchFix', and 'Thread'. Third, the insights gained from artificial intelligence and big data help create new fashion retailing platforms such as 'Botshop' and 'Lyst'. Last, artificial intelligence and big data assist with design. 'Ivyrevel' designs digital fashion, assisted by a macroscopic perspective on fashion trends, market and consumers through the analysis of big data. The Fourth Industrial Revolution brings changes across all industries that will likely accelerate. The fashion industry is also undergoing many changes with advancements in scientific technology. The convergence of big data and artificial intelligence will play a key role in the future of fast-moving industry like fashion, where fickle tastes of consumers are the main drivers.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.347-354
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• 2023

The rapid development of information technology has accelerated the application of big data and the Internet of Things in various industries. Big data has a great potential in the development of smart tourism. With the help of innovation in emerging technologies such as big data and Internet of Things, smart tourism has a better possibility to surpass traditional tourism. Therefore, this article provides a theoretical support to this process. It has explored the innovative management model of big data and IoT in smart tourism and evaluate their effects on promoting tourism. It offers a reference for the integration and innovation of the tourism theory system. Before big data technology, the development of Internet boosted online tourism. However, tourism marketing is still inefficient due to a lack of understanding about tourists. After many practical explorations of big data technology, tourism websites begin to adopt big data technology in their daily operations. With the changes in tourists' preferences and needs, further innovation and research are needed to help smart tourism keep up with the changes in the market and create more competitive products and services. Innovation serves as the driving force for enterprises to occupy the market and develop.

• 대한조선학회논문집
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• 제55권3호
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• pp.243-251
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• 2018

In the shipyard, a lot of data is generated, stored, and managed during design, construction, and operation phases to build ships and offshore structures. However, it is difficult to handle such big data efficiently using existing data-handling technologies. As the big data technology is developed, the ship and offshore industries start to focus on the existing big data to find valuable information from it. In this paper, the material requirement estimation method of offshore structure piping materials using big data analysis is proposed. A big data platform for the data analysis in the shipyard is introduced and it is applied to the analysis of material requirement estimation to solve the problems in piping design by a designer. The regression model is developed from the big data of piping materials and verified using the existing data. This analysis can help a piping designer to estimate the exact amount of material requirement and schedule the purchase time.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.290-296
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• 2022

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.19-20
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• 2015

Since 2013, Seoul Metropolitan Government (SMG) has introduced big data initiatively in administration and put into practices in transportation, safety, welfare in order to overcome limited resources and conflicting interests. For establishing a new midnight bus service, SMG prepared optimized midnight bus routes by analyzing big data from mobile phone Call Data Record (CDR) through collaboration with a telecommunication company. Despite of limited budget and resources, newly identified routes can cover over 42% of the citizen with 9 routes and less than 1% of buses compare with day time operation. In addition to solve transportation problem, SMG utilizes big data to resolve location selection problem for choosing new facility locations such as life double cropping centers and senior citizen leisure centers. As results, SMG demonstrates big data as a good tool to make policies and to build smarter city by overcome space-time limitation of resources, mediation of conflicts, and maximizes benefit of the citizen.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.381-389
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• 2022

With the collection of huge volumes of text, image, audio, video or combinations of these, in a word multimedia data, the need to explore them in order to discover possible new, unexpected and possibly valuable information for decision making was born. Starting from the already existing data mining, but not as its extension, multimedia mining appeared as a distinct field with increased complexity and many characteristic aspects. Later, the concept of big data was extended to multimedia, resulting in multimedia big data, which in turn attracted the multimedia big data mining process. This paper aims to survey multimedia data mining, starting from the general concept and following the transition from multimedia data mining to multimedia big data mining, through an up-to-date synthesis of works in the field, which is a novelty, from our best of knowledge.

• 유통과학연구
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• 제21권1호
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• pp.53-63
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• 2023

Purpose: Big Data analytics (BDA) has been recognized to improve firm performance because it can efficiently manage and process large-scale, wide variety, and complex data structures. This study examines the determinants of Big Data analytics adoption toward marketing and financial performance of global logistic companies in Thailand. The research framework is adopted from the technology-organization-environment (TOE) model, including technological factors (relative advantages), organizational factors (technological infrastructure and absorptive capability), environmental factors (industry competition and government support), Big Data analytics adoption, marketing performance, and financial performance. Research design, data, and methodology: A quantitative method is applied by distributing the survey to 450 employees at the manager's level and above. The sampling methods include judgmental, stratified random, and convenience sampling. The data were analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The results showed that all factors significantly influence Big Data analytics adoption, except technological infrastructure. In addition, Big Data analytics adoption significantly influences marketing and financial performance. Conversely, marketing performance has no significant influence on financial performance. Conclusions: The findings of this study can contribute to the strategic improvement of firm performance through Big Data analytics adoption in the logistics, distribution, and supply chain industries.

• 정보화정책
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• 제23권1호
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• pp.3-19
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• 2016

본 연구의 목적은 빅데이터 보안 분야의 기존 연구를 분석하고, 향후 연구 방향을 모색하는 것이다. 이를 위해 국내외의 총62편의 논문을 식별하여, 발간년도, 게재 매체, 전반적인 연구접근 방법, 세부적 연구 방법, 연구 주제 등을 분석하였다. 분석 결과, 빅데이터 보안 연구는 매우 초기 단계로서, 비실증 연구가 압도적인 비중을 차지하고 있고, 관련 개념/기법에 대한 이해를 해나가는 과정으로서 기술-관리-통합의 단계로 진화한 정보보안 분야의 연구 동향에 동조하여 기술적인 연구가 주로 진행되고 있다. 연구 주제 측면에서도 빅데이터 보안에 대한 전반적인 이슈를 다룬 총론적인 연구들이 보안 구현 방법론, 분야별 이슈 등의 각론적 연구에 비해 높은 비중을 나타내는 등 초기 단계의 모습을 나타내고 있다. 향후 유망한 연구 분야로는 빅데이터 보안에 대한 전반적인 프레임워크 수립, 업종별 빅데이터 보안에 대한 연구, 빅데이터 보안 관련 정부 정책 분석 등을 들 수 있다. 빅데이터 보안 분야의 연구는 본격적으로 시작된 지 얼마 되지 않아, 연구 결과가 상대적으로 매우 부족한 편이다. 앞으로 다양한 관점에서 빅데이터 보안과 관련해 풍부한 주제를 다루는 연구가 진행되기를 기대한다.

• 디지털융복합연구
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• 제19권10호
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• pp.143-149
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• 2021

초연결 지능정보사회에 빠른 진입으로 빅데이터 기반의 자원관리 등을 위한 빅데이터시스템 구축의 필요성을 대두되면서, 공공기관에서 빅데이터시스템 구축을 추진하고 있는 실정이다. 이에, 본 연구는 공공기관 현실에 맞는 빅데이터시스템 구축 시 고려해야할 측정항목을 도출하고자 한다. 고등교육기관 통합정보시스템 구축의 환경요인 측정항목에 선행연구를 기반으로 빅데이터 관련연구들의 성공요인들과 공공기관 빅데이터 시스템 구축의 특성을 분석·결합하였다. 연구방법으로는 빅데이터 전문가들을 대상으로 델파이 방법등을 사용하여 빅데이터 특성이 반영된 19개 측정항목을 도출하였으며, 이를 빅데이터시스템에 구축하고자 하는 공공기관에 성공적으로 적용하기 위한 방안을 제언하였다. 본 연구결과가 공공기관에서 성공적인 빅데이터시스템 구축의 기초 자료로 활용되기를 기대한다.