• The Journal of Bigdata
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• v.7 no.2
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• pp.75-90
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• 2022

Recently, complex and sophisticated analysis of transportation is required due to changes in the socioeconomic environment and the development of bigdata technology. Especially, the revision of 3 laws including PERSONAL INFORMATION PROTECTION ACT makes it possible to combine various types of mobility data. But strengthen personal information protection makes inefficiency in utilizing mobility bigdata. In this paper, we proposed the "Virtual fusion methdology via mobility bigdata" which is a methodology for indirect data fusion for various mobility bigdata such as mobile data and transportation card data, in order to resolve legal restrictions and enable various transportation analysis. And we also analyzed regional bus passenger in Seoul capital area and Cheongju city with aforementioned methodology for verification. This methdology could analyze behavioral pattern of passenger with the MCGM(Mobility Comprehensive Genetic Map), graph with position and time, making with mobile data. Consquently, using MCGM, which is a result for indirect data fusion, makes it possible to analyze various transportation problems.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.353-376
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• 2008

The main purpose of this research is to develop a methodology for designing metadata application profiles(AP) and to design a comprehensive AP for Korea Art and Education Service(KACES), The process of developing a methodology is divided into three steps, analysis of standard metadata schema, analysis of user needs, and content analyses. Metadata principles and guidelines were utilized in designing a KACES AP along with the developed methodology in this study. This paper describes what role the methodology developed here plays in devising metadata elements. The paper also discusses the benefits of three methods for AP design. The study has values in that it provides implications for designing APs for other domains.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1007-1023
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• 2016

This paper explores the conditions and potential of newly designed and tried methodology of big data analysis that apply to Korean history subject matter. In order to advance them, we need to pay more attention to quantitative analysis methodologies over pre-existing qualitative analysis. To obtain our new challenge, I propose 'digital history' methods along with associated disciplines such as linguistics and computer science, data science and statistics, and visualization techniques. As one example, I apply interdisciplinary convergence approaches to the principle and mechanism of elite reproduction during the Korean medieval age. I propose how to compensate for a lack of historical material by applying a semi-supervised learning method, how to create a database that utilizes text-mining techniques, how to analyze quantitative data with statistical methods, and how to indicate analytical outcomes with intuitive visualization.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2002.11a
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• pp.633-636
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• 2002

현대는 정보의 홍수라고 할 만큼 많은 정보들이 존재하는 정보화 사회로서 정보 경쟁력이 중요시되는 시대이다. 이에 발맞춰 이러한 정보를 운영하는 정보시스템의 안전성이 많은 조직에서 이슈가 되고, 자신의 조직의 정보 자산을 보호하기 위한 방법을 모색한다. 이러한 방법 중 가장 광범위하게 적용되는 방법이 조직의 자산에 대한 위험분석이다. 위험 분석은 조직에 내재되어 있는 위협, 취약성을 식별하고, 식별된 위협 및 취약성에 대하여 보호대책을 강구함으로써 안전한 정보시스템 운영을 가능케 한다. 그러나 아직까지 외국의 위험분석 방법론에도 데이터 자산의 위험분석 방법을 구체적으로 기술이 되어 있지 않기 때문에, 실제로 데이터 자산의 위험 분석은 굉장히 힘들다. 그러므로 본 논문은 업무 중심의 위험분석 방법론과 이 방법론의 프로세스를 따라 데이터 자산의 위험분석 수행방법을 제안한다.

• Smart Media Journal
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• v.12 no.9
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• pp.116-123
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• 2023

In this study, I will describe the difference in operating methods centered on the game operating system between beginners and expert groups in MORPG PC games and focus on the methodology to analyze them. First of all, a hypothesis was established to distinguish between beginners and expert groups based on the manipulation system of character movements commonly used in MORPG, and through this distinction, it was analyzed whether finger movement data and key stroke data related to the manipulation system can be significantly used in the future. Based on these analysis results, it was found that the analysis methodology that combines finger motion data and key stroke analysis is meaningful as a user test methodology for the PC MORPG game operating system in the future.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.103-114
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• 2021

This study explores research methodologies of design and data science, and applies data science paradigm on design process. Design research methodologies would have benefits of productivity and efficiency by using data driven design methodology. From insights of former studies, a new methodology of data driven design is suggested that design problem is transformed to data set attributes, such as variables, values and data patterns. The fine dust information app design is conducted as a case study to prove this methodology.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.251-262
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• 2010

While outsourcing has become a basic strategy of the information system adoption, there is an emerging needs to analyze the gap between the required data and the existing data for the new system from an adopting company's perspective. In CRM adoption failure cases, the first reason is adopting company pay no attention to the data that will support investment and systems. So far, there is no attempt to consider data driven approach in information system adoption field. Hence, we propose Information System Adoption Model based on Data (ISAMD) and show how to use in real world by simulation. By using ISAMD, information system adoption decision maker can simulate the needed data and related cost with various information system alternatives in short term, and long term planning. ISAMD can prevent the possible threat of unexpected data cost in adopting new system at the adopting decision stage.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.142-144
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• 2002

데이터 웨어하우스는 기업의 의사 결정을 지원하기 위해 기업의 운영 데이터베이스로부터 추출한 데이터의 집합으로써 OLAP 분석에 이용된다. OLAP은 이들 데이터를 다양하게 분석할 수 있도록 다차원 데이터로 표현하고 이를 활용하여 복잡한 분석 질의 처리 및 다차원 데이터 분석에 활용한다. 이러한 OLAP의 다차원 데이터를 관계형 데이터베이스에서 표현하기 위해 스타 스키마가 널리 사용된다. 또한 다차원 데이터와 데이터 웨어하우스는 방대한 분량를 갖는 전체 기업의 데이터를 표현하고 있어 이를 설계하는 것이 매우 복잡하고 많은 노력이 소요된다. 따라서 이를 설계하기 위한 체계적인 설계 방법론이 필요하다. 데이터 웨어하우스의 원천 데이터가 되는 운영 데이터베이스는 현재 ER 도형을 이용하여 개념적인 방법으로 널리 설계되고 있다. 따라서 이 논문에서는 ER 도형으로 설계된 운영 데이터베이스로부터 데이터 웨어하우스를 설계하는 개념적인 방법론을 제시한다. 이에 따라 OLAP 분석을 위해 사용할 수 있는 다양한 유형의 스타 스키마에 대해 ER 도형으로 표현/변환하는 방법을 제시한다. 이를 통해 자신이 원하는 다차원 데이터를 얻기 위해 유지해야 할 데이터 웨어하우스를 ER 도형을 이용하여 개념적으로 편리하게 설계하는 방법/지침을 제공하며, 나아가 해당 유형의 스타 스키마가 갖는 의미를 개념적으로 쉽게 전달할 수 있도록 하였다.

• Journal of the Korean Geographical Society
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• v.48 no.5
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• pp.768-785
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• 2013

Count data aggregated into areal units such as administrative boundaries are the most important sources of information for geographic research. Despite of ongoing research on spatial cluster analysis of count data, it has received relatively little attention and besides, it is difficult to comprehend research trends as well as major outcomes and challenges. This study aims to review the research literature conducted during the last two decades, to examine methodological characteristics, and finally to discuss some issues and challenges. Methods for indentifying spatial clusters have been used in various fields including geography, criminology, and epidemiology. However, their methodological features are not only quite distinct from each other, but there are issues related to the statistical reliability. Therefore, these have to be taken into account carefully when particular methods are used, and further empirical research about methodological issues and the development of analysis tools is needed.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.80-93
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• 2022

This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.