• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

• Convergence Security Journal
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• v.21 no.1
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• pp.73-78
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• 2021

Big data is a key driver of the fourth industrial revolution, represented by ultra-connected, ultra-intelligence, and ultra-convergence, and it is important to create innovation and share, link, and utilize data to discover business models. However, it is difficult to secure and utilize high-quality and abundant data when big data platforms are built in a regular manner without considering shared-linked. Therefore, this paper presents the development direction of big data platform infrastructure by comparing and analyzing various cases of big data platforms to enable data production, construction, linkage, and distribution.

• Journal of Information Technology Applications and Management
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• v.20 no.4
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• pp.1-18
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• 2013

Big data has become a worldwide topic. Despite this, big data accurately understand and acquire the business to take advantage of companies that were only very few. The purpose of this study is to investigate the factors that effect Korean firm's adopting big data system. Empirical test was conducted to verify hypotheses using extended technology acceptance model and we analyzed factors which affect the behavioral intention of big data System. Based upon previous researches, we have selected organization innovation, organization slank, organization information system infra maturity, perceived benefits of big data system, perceived usefulness, perceived ease of use, behavioral intention as variables and proposed a research model based on survey questionnaires. From those, we drew that perceived usefulness and perceived ease of use influenced the behavioral intention. The results of this study will increase the users' awareness on big data system and contribute to develop a way to enable the introduction of new technologies.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.445-451
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• 2013

Cyber terrorism has lately aimed at major domestic financial institutions and broadcasters. A large number of PCs have been infected, so normal service is difficult. As a result, the monetary damage was reported to be very high. It is important to recognize the importance of big data. But security and privacy efforts for big data is at a relatively low level, therefore the marketing offort is very active. This study concerns the analysis of Big Data industry and Big data security threats that are intelligent and the changes in defense technology. Big data, security countermeasures for the future are also presented.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.207-215
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• 2016

The demand for spatial data service technologies is increasing lately with the development of realistic 3D spatial information services and ICT (Information and Communication Technology). Research is being conducted on the real-time provision of spatial data services through a variety of mobile and Web-based contents. Big data or cloud computing can be presented as alternatives to the construction of spatial data for the effective use of large volumes of data. In this paper, the process of building HLM (Hyper Live Map) using multi-source data to acquire stereo CCTV and other various data is presented and a big data service architecture design is proposed for the use of flexible and scalable cloud computing to handle big data created by users through such media as social network services and black boxes. The provision of spatial data services in real time using big data and cloud computing will enable us to implement navigation systems, vehicle augmented reality, real-time 3D spatial information, and single picture based positioning above the single GPS level using low-cost image-based position recognition technology in the future. Furthermore, Big Data and Cloud Computing are also used for data collection and provision in U-City and Smart-City environment as well, and the big data service architecture will provide users with information in real time.

• Spatial Information Research
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• v.21 no.5
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• pp.43-51
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• 2013

In this study, the concept of spatial big data and effective ways to build a spatial big data system are presented. Big Data is defined as 3V(volume, variety, velocity). Spatial big data is the basis for evolution from 3V's big data to 6V's big data(volume, variety, velocity, value, veracity, visualization). In order to build an effective spatial big data, spatial big data system building should be promoted. In addition, spatial big data system should be performed a national spatial information base, convergence platform, service providers, and providers as a factor of production. The spatial big data system is made up of infrastructure(hardware), technology (software), spatial big data(data), human resources, law etc. The goals for the spatial big data system build are spatial-based policy support, spatial big data platform based industries enable, spatial big data fusion-based composition, spatial active in social issues. Strategies for achieving the objectives are build the government-wide cooperation, new industry creation and activation, and spatial big data platform built, technologies competitiveness of spatial big data.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.317-323
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• 2016

Big Data is now seen as a major asset in the company's competitiveness, its influence in the future is expected to grow. Companies that recognize the importance are already actively engaged with Big Data in product development and marketing, which are increasingly applied across sectors of society, including politics, sports. However, lack of knowledge of the system implementation and high costs are still a big obstacles to the introduction of Big Data and systems. It is an objective in this study to build a Big Data system, which is based on open source Hadoop and Hive among Big Data systems, utilizing POS sales data of small and medium-sized offline markets. This approach of convergence is expected to improve existing sales systems that have been simply focusing on profit and loss analysis. It will also be able to use it as the basis for the decisions of the executive to enable prediction of the consumption patterns of customer preference and demand in advance.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.23 no.3
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• pp.201-209
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• 2017

The Big Data, the element of the Fourth Industrial Revolution, is drawing attention as the 4th Industrial Revolution is mentioned in the 2016 World Economic Forum. Big Data is being used in various fields because it predicts the near future and can create new business. However, utilization and research in the field of packaging are lacking. Today packaging has been demanded marketing elements that effect on consumer choice. Big data is actively used in marketing. In the marketing field, big data can be used to analyze sales information and consumer reactions to produce meaningful results. Therefore, this study proposed a method of applying big data in the field of packaging focusing on marketing. In this study suggest that try to utilize the private data and community data to analyze interaction between consumers and products. Using social big data will enable to understand the preferred packaging and consumer perceptions and emotions in the same product line. It can also be used to analyze the effects of packaging among various components of the product. Packaging is one of the many components of the product. Therefore, it is not easy to understand the impact of a single packaging element. However, this study presents the possibility of using Big Data to analyze the perceptions and feelings of consumers about packaging.

• Asia pacific journal of information systems
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• v.26 no.1
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• pp.66-79
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• 2016

The availability of detailed data on customers' online behaviors and advances in big data analysis techniques enable us to predict consumer behaviors. In the past, researchers have built purchase prediction models by analyzing clickstream data; however, these clickstream-based prediction models have had several limitations. In this study, we propose a new method for purchase prediction that combines information theory with machine learning techniques. Clickstreams from 5,000 panel members and data on their purchases of electronics, fashion, and cosmetics products were analyzed. Clickstreams were summarized using the 'entropy' concept from information theory, while 'random forests' method was applied to build prediction models. The results show that prediction accuracy of this new method ranges from 0.56 to 0.83, which is a significant improvement over values for clickstream-based prediction models presented in the past. The results indicate further that consumers' information search behaviors differ significantly across product categories.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.8
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• pp.399-408
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• 2016

As entering the Big Data age, utilization of Big Data is also increasing in the intellectual property sector. Meanwhile, the purpose of a trademark which distinguishes the source of the goods essentially is to enable the public to recognize the goods. Big Data technologies which is recently becoming a issue can be used as a tool to judge consumer's awareness of the trademark. It was difficult for judgment of trademark awareness through traditional ways. As a new way, survey methodology has bee received attention, and it was applied to the field of trademark law. However, various problems such as cost, time, objectivity, and fairness were observed. In order to overcome theses limitations, this study proposes new way utilizing big data analytics for judgment on consumer's awareness of the trademark. This new way will not only contribute to enhancing the objectivity of judging trademark awareness but also utilized to support for related legal judgments.