• Journal of The Korean Association of Information Education
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• v.26 no.2
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• pp.141-151
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• 2022

Recently, basic literacy education related to digital literacy and data literacy has been emphasized for students who will live in a rapidly developing future digital society. Accordingly, demand for education to improve big data and data literacy is also increasing in general universities and universities of education as basic knowledge. Therefore, this study designed and applied big data analysis courses for pre-service teachers and analyzed the impact on data literacy. As a result of analyzing the interest and understanding of the input program, it was confirmed that it was an appropriate form for the level of pre-service teachers, and there was a significant improvement in competencies in all areas of 'knowledge', 'skills', and 'values and attitudes' of data literacy. It is hoped that the results of this study will contribute to enhancing the data literacy of students and pre-served teachers by helping with systematic data literacy educational research.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.815-821
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• 2021

The advantage of big data is to collect a large amount of data on the Internet and refine and use valuable data. That is, the unstructured data is processed so that the user can analyze and utilize it from a necessary point of view. This paper is a relatively small project and is based on unstructured data that can be closely applied to real life and used for marketing. The subjects of the experiment were modeled on lodging companies in the Seoul metropolitan area an hour away from Seoul, and analyzed for the increase in lodging rates before and after marketing using big data. As an experiment that shows the effects of increasing sales, reducing costs, and increasing returns by users, we propose a system to determine and filter whether data input in the process of analyzing big data such as social networks can be used as accommodation-related information.

• Journal of Platform Technology
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• v.12 no.3
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• pp.3-15
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• 2024

Knowledge mining is a research field that applies various techniques such as data modeling, information extraction, analysis, visualization, and result interpretation to find valuable knowledge from diverse large datasets. It plays a crucial role in transforming raw data into useful knowledge across various domains like business, healthcare, and scientific research etc. In this paper, we propose analytical techniques for performing knowledge discovery and data mining from various data by extending the Formal Concept Analysis method. It defines algorithms for representing diverse formats and structures of the data to be analyzed, including models such as many-valued data table data and triadic data table, as well as algorithms for data processing (dyadic scaling and flattening) and the construction of concept hierarchies and the extraction of association rules. The usefulness of the proposed technique is empirically demonstrated by conducting experiments applying the proposed method to public open data.

• (The) Korean Journal of Advertising
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• v.27 no.4
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• pp.71-90
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• 2016

Managers of firms often wonder whether advertising expenditure is a mere expense or an investment with foreseeable future returns. When top management makes a decision on the level of advertising expense, it must consider whether an increase in advertising spending will positively affect brand loyalty and the increased brand loyalty will positively affect profitability and firm value. We investigate the industry-specific effects of advertising spending on marketing and the effect of loyalty on financial performances using top companies in Korea, specifically, 184 firms' data from year 1998 to 2014. The empirical results of a fixed effect model indicate that the effects of advertising on customer satisfaction index and loyalty on the firms' financial performance are positive. In service industry, unlike manufacturing industry, advertising has a significantly positive effect Brand Loyalty. In addition, Brand Loyalty had positive impacts on ROA and ROE as profitability index, and Tobin's q, a market-value index. The research results suggest that advertising in service industry should be considered as customer satisfaction investment and the increased Brand Loyalty as a profit for present and a business investment for the future respectively.

• Smart Media Journal
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• v.6 no.3
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• pp.83-88
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• 2017

The data analysis system using Big-data is worthy to be used in various fields such as politics, traffic, natural disaster, shopping, customer management, medical care, and weather information. Particularly, the analysis of the momentum of an individual using an acceleration signal collected from a wearable device has already been widely used. However, since the data used in such a system stores only the data necessary for measuring the individual activity, it does not provide various analysis results other than the exercise amount of the individual. In this paper, I propose a system that analyzes collective behavior pattern and activity based on the acceleration signal that can be collected from personal smartphones for 24 hours a day and stored in big data. I also propose a system that sends acceleration signals and receives analysis results using standard messaging to use on various smart devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.69-71
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• 2022

The 4th industrial revolution is regarded as a paradigm that determines future national competitiveness through the convergence and intelligence of various ICT technologies. In order to ensure the realization of the Korean military's national tasks and the successful implementation of Defense Reform 2.0, the vision for the promotion of the 'Defense Innovation Plan in the Era of the 4th Industrial Revolution' was set as 'implementation of smart defense innovation based on the 4th industrial revolution'. However, it is time to review whether the data value chain, which is the core of the 4th industrial revolution, is considered before full-scale business promotion according to the vision. In this paper, we compared and analyzed the smart defense innovation promotion project and the military and pan-government data platform project in terms of the data value chain, and suggested policy alternatives to build a defense data ecosystem.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.2
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• pp.27-48
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• 2023

In domestic public institutions, administrative information datasets are recognized as electronic records that require systematic management. In this regard, concrete measures for the execution of records management have been discussed recently in the National Archives of Korea and the academic field. This study seeks to derive a plan to improve evaluation indicators that can effectively grasp the value of administrative information datasets and the matters to be considered when evaluating and selecting datasets in the records management of public institutions. This paper analyzes the theoretical background and current status of dataset evaluation and selection, derives considerations necessary for this process, and proposes improvement measures for evaluation indicators presented in previous studies. The results of this study are expected to lead to the revitalization of discussions on maintaining the public institutions' dataset management system and supplementing the management process in the future.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.208.2-208.2
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• 2010

폐기물 가스화는 생산된 합성가스를 이용하여 발전 등 직접적인 에너지원으로 이용할 수 있으며, 고부가가치 화합물의 원료 공급원으로도 이용할 수 있다. 폐기물 가스화를 이용한 고부가가치 화합물 제조의 경우 기존 화합물 제조공정에 폐기물 가스화 공정이 연계되어, 하나의 복합시스템으로 운영이 된다. 따라서 기존 공정과 최적으로 연계될 수 있는 폐기물 가스화 시스템의 개발 또는 선정이 필요하며, 이를 위하여 폐기물 가스화 시스템에 대한 분석 평가가 적절하게 이루어져야 한다. 본 연구에서는 시스템공학 개념을 적용하여 폐기물 가스화 시스템의 체계적인 분석 평가를 위한 프레임워크를 개발하였다. 시스템공학은 요건분석, 기능분석, 합성(통합), 분석/관리 프로세스를 통하여 시스템을 성공적으로 구현하기 위한 다학제적인 접근방법이다. 이러한 시스템공학의 개념 및 기본 프로세스를 적용 조정하여 폐기물 가스화 분석 평가 프레임워크를 개발하였으며, 개발된 프레임워크는 계층구조로 표현이 된다. 계층구조는 분석관점, 분석항목, 분석지표로 구성이 되며 분석된 데이터에 대한 평가는 AHP를 통하여 계산된 가중치를 적용하여 이루어진다.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.133-141
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• 2021

This research suggests a design process that effectively complements the human-centered design through an objective data-driven approach. The subjective human-centered design process can often lack objectivity and can be supplemented by the data-driven approaches to effectively discover hidden user needs. This research combines the data mining analysis with co-design process and verifies its applicability through the case study on the smart heating jacket. In the data mining process, the clustering can group the users which is the basis for selecting the target groups and the decision tree analysis primarily identifies the important user perception attributes and values. The broad point of view based on the data analysis is modified through the co-design process which is the deeper human-centered design process by using the developed workbook. In the co-design process, the journey maps, needs and pain points, ideas, values for the target user groups are identified and finalized. They can become the basis for starting new product development.