• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• KNOM Review
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• v.22 no.2
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• pp.12-21
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• 2019

There is a rapid development of experimental equipment and ICT technology in data-intensive scientific areas, thus, big data of more than exabyte size is being generated. However, the big data transmission technology does not satisfy the needs of the application researchers who utilize it. Various high-performance transmission technologies have been developed based on QoS(Quality of Service), but they also require changes in the clean slate method. On the other hand, ScienceDMZ technologies improve the performance of scientific big data transmission by bypassing the firewall that causes a big problem in transmission performance. In addition, it is possible to implement without changing the existing network. In this paper, we built ScienceDMZ in an international long-distance environment based on KREONET(Korea Research Environment Open NETwork), and we verified the performance. We also introduced how GPU platform could be linked in a distributed ScienceDMZ environment.

• The Journal of Small Business Innovation
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• v.20 no.3
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• pp.49-68
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• 2017

Platform finance is emerging as an alternative finance for SMEs by suggesting a new funding source based on a new technology named FinTech. The essence of this business is the adapting ICT challenges to the financial industry that can adequately reflect risk assessment using Big Data and effectively meet individual risk-return preference. Thus, this is evolving as an alternative to existing finance in the form of P2P loans for Micro Enterprises and supply-chain finance for SMEs that need more working capital. Platform finance in Korea, however, is still at an infant stage and requires policy support. This can be summarized as follows: "Participation of institutional investors and the public sector," meaning that public investors provide seed money for the private investors to crowd in for platform finance. "Negative system in financial regulations," with current regulations to be deferred for new projects, such as Sandbox in the UK. In addition, "Environment for generous use of data," allowing discretionary data sharing for new products," and "Spreading alternative investments," fostering platform finance products as alternative investments in the low interest-rate era.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.315-325
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• 2016

Due to the expansion of data and technical progress in the military industry, it is important to extract meaningful information for assuring quality and making policies. The analysis of trends and decision making based on big data is helpful for increasing productivity in business and finding new business opportunities. We propose an application to collect reliable quality information for munitions and build a big data platform for using the accumulated information and numerical data. We verified the proposed platform using the Test Report Information Service (TRIS) system and suggest a method that utilizes unstructured and semi-structured data accumulated by TRIS. Thus, we expect that the proposed platform will help in building infrastructure for military data, making efficient strategies, and analyzing trends for assuring munitions quality.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.15-28
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• 2022

Recently, government agencies are actively adopting the platform model as a means of public policy. However, existing studies on the public platform are minimal and have focused on user experiences or the possibility of public usage of the platform model. Now the research concerning building governance structure and utilizing network effects of the platform after adopting the platform model in the public sector is keenly required. This study intended to ignite academic dialogue on the governance of public platforms in the context of digital transformation. This study focused on a case of the 'Special delivery,' a public delivery app established by Gyeonggi-do. In order to analyze the characteristics of the public platform and its governance structure, data were collected from press releases, policy reports, and news articles. Data was analyzed using the frame of Hagui's platform design factors and Ansell & Gash's collaborative governance model. The results of the public platform analyses showed 1) incompleteness in the value trade-off accounting, which was designed for platform business based on general cost-benefit analysis, and 2) a closed governance structure that limits direct participation of diverse user groups(i.e., service provider, customer) in order to enhance providers' utility by preventing customers' excessive online activities. The results of this study provided theoretical and policy implications regarding designing the strategy for accounting for value trade-offs and functioning governance structure for public platforms.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.8
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• pp.235-242
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• 2020

In order to promote digital transformation of our agricultural and rural communities in the wake of the fourth industrial revolution and prepare for the upcoming artificial intelligence era, it is necessary to establish a system and system that can collect, analyze and utilize necessary quality data. To this end, we will investigate and analyze problems and issues felt by various stakeholders such as farmers and agricultural officials, and present strategic measures to revitalize big data, which must be decided in order to promote digital transformation of our agricultural and rural communities, such as expanding big data platforms for joint utilization, establishing sustainable big data governance, and revitalizing the foundation for big data utilization based on demand.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.716-722
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• 2016

In the recent rapidly changing IT environment, the amount of smart digital data is growing exponentially. As a result, in many areas, utilizing big data research and development services and related technologies is becoming more popular. In SMART learning, big data is used by students, teachers, parents, etc., from a perspective of the potential for many. In this paper, we describe big data and can utilize it to identify scenarios. Big data, obtained through customized learning services that can take advantage of the scheme, is proposed. To analyze educational big data processing technology for this purpose, we designed a system for big data processing. Education services offer the measures necessary to take advantage of educational big data. These measures were implemented on a test platform that operates in a cloud-based operations section for a pilot training program that can be applied properly. Teachers try using it directly, and in the interest of business and education, a survey was conducted based on enjoyment, the tools, and users' feelings (e.g., tense, worried, confident). We analyzed the results to lay the groundwork for educational use of big data.

• Informatization Policy
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• v.25 no.4
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• pp.108-120
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• 2018

With the rise of the Fourth Industrial Revolution and I-Korea 4.0, both of which pursue strategies for industrial innovation and for the solution to social problems, the real estate industry needs to change in order to make effective use of available space in smart environments. The implementation of smart spaces is a promising solution for this. The smart space is defined as a good use of space, whether it be a home, office, or retail store, within a smart environment. To enhance the use of smart spaces, efficient decision-making and well-timed and accurate interaction are required. This paper proposes a smart space based on platform which takes advantage of emerging technologies for the efficient storage, processing, analysis, and utilization of big data. The platform is composed of six layers - collection, transfer, storage, service, application, and management - and offers three service frameworks: activity-based, market-based, and policy-based. Based on these smart space services, decision-makers, consumers, clients, and social network participants can make better decisions, respond more quickly, exhibit greater innovation, and develop stronger competitive advantages.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.1-8
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• 2020

The use of text data in big data analytics has been increased. So, much research on methods for text data analysis has been performed. In this paper, we study Bayesian learning based on conjugate prior for analyzing keyword data extracted from text big data. Bayesian statistics provides learning process for updating parameters when new data is added to existing data. This is an efficient process in big data environment, because a large amount of data is created and added over time in big data platform. In order to show the performance and applicability of proposed method, we carry out a case study by analyzing the keyword data from real patent document data.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.1
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• pp.47-61
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• 2022

In this study, We developed VR (Virtual Reality) geological resources based on the Geo Big Data of the Big Data platform that provided by the Korea Institute of Geoscience and Mineral Material (KIGAM). So students selected the theme of lessons by using these resources and we operated Remote classes using the materials that developed as to Virtual Reality. Therefore, the geological theme maps provided by the Geo Big Data Open Platform were reconstructed and produced materials were created for Study about Real Korean geological outcrops grounded in Virtual Reality. And Topographic information data was used to produce class materials for Remote classes. Twenty students were selected by Random sampling, and data were collected by conducting a survey including interviews to confirm the change in students' perception of remote classes in virtual reality geological data development and the effect of the classes, so data were analyzed through inductive categorization. The results of this study are as follows. First, students showed positive responses in terms of interest, utilization, and knowledge utilization as taking remote classes for developing geological data in virtual reality geological data. This is the result of showing the adaptability of diverse and flexible learning getting away from a fixed framework by motivating and encouraging students and inducing cooperation for communication. Second, students recognized distance education in the development of Virtual Reality geological data as 'Realistic hands-on learning process', 'Immersive learning process by motivation', and 'Learning process of acquiring knowledge in the field of earth science'.