• Journal of Technology Innovation
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• v.31 no.1
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• pp.65-103
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• 2023

With the recent surge in the share of data-based economic activities, there have been vibrant discussions on the data economy. Yet, few extant works provide a framework for systematically analyzing the transition to the data economy by major industries in Korea. By reviewing the existing literature, we first summarize the main characteristics of the data economy as building platforms, the greater importance of predictive power, and the increased use of new analytics. Next, based on such understanding, we provide a comparative analysis regarding the degree of data-based activities in Korea's financial, real estate, and medical sectors. We find that the speed at which, and the content of the data economy characteristics being realized were different for the different sectors. These findings suggest that differentiated policy approaches by major industrial sectors such as finance, real estate, and medical care are needed to improve economic productivity and increase welfare through the spread of the data economy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.227-230
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• 2015

For analyzing and prediction of economic trends, it is necessary to collect particular economic news and stock data. Typical Web crawler to analyze the page content, collects document and extracts URL automatically. On the other hand there are forms of crawler that can collect only document of a particular topic. In order to collect economic news on a particular Web site, we need to design a crawler which could directly analyze its structure and gather data from it. The wrapper-based web crawler design is required. In this paper, we design a crawler wrapper for Economic news analysis system based on big data and implemented to collect data. we collect the data which stock data, sales data from USA auto market since 2000 with wrapper-based crawler. USA and South Korea's economic news data are also collected by wrapper-based crawler. To determining the data update frequency on the site. And periodically updated. We remove duplicate data and build a structured data set for next analysis. Primary to remove the noise data, such as advertising and public relations, etc.

• Information and Communications Magazine
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• v.29 no.11
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• pp.48-54
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• 2012

정보통신 기술은 아날로그 산업에서 디지털 산업을 거쳐 현재는 스마트 산업으로 이어지는 수단으로 활용되어 왔다. 특히 산업 사회생활에서 문서로 직접 주고받던 환경에서 메일, 전자문서 교환 등으로 바뀌면서 편리성과 비용절감을 통해 산업 사회생활 발전에 기여하고 있다. 최근 빅데이터 기술은 대용량 정보를 분석하여 기상예측, 신약개발, 유전자 분석 등의 다양한 분야에 활용되고 있다. 그러나 대용량 정보 안에는 개인 식별을 할 수 있는 정보가 포함되어 있어, 빅데이터 기술을 바로 적용하기에는 개인정보보호법이 정하는 개인정보보호 이용에 관한 법률에 대한 준비가 미흡한 실정이다. 예를 들어 공공기관의 데이터를 활용하여 날씨 예측, 재난 방재 서비스 등을 통해 국민의 삶을 제고함과 동시에 경제적으로 많은 이익을 가져올 수 있다. 그러나 개인정보를 타인이 악의적으로 이용할 수 있어 개인에게 경제적, 정신적 피해를 줄 수 있다. 또한 개인정보의 노출은 과거와 달리 삭제되거나 잊혀지지 않고 영구적으로 재사용이 가능하기 때문에 이를 사전에 막을 수 있는 방법이 필요하다. 이에 본고는 빅데이터 등장에 따른 시장구조 변화 및 경제적 파급효과를 분석하고, 법리적 분석을 바탕으로 빅데이터 기술이 올바르게 시장에 정착할 수 있은 법(규제)방안을 제시하고자 한다.

• Review of Korea Contents Association
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• v.15 no.1
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• pp.14-20
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• 2017

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1313-1325
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• 2017

Economic statistics such as GDP, consumer prices, balance of payments, and unemployment rates are regularly measured over time. One of the best way to understand economic statistics is to visualize economic statistics as a picture. This makes it easier to grasp patterns of economic statistics and to communicate with users. The web technologies and the visualization tools make it possible to create dynamic and interactive visualization of economic statistics. Statistics Korea and the Bank of Korea provide various data visualization relating to official statistics such as infographics and dynamic charts. This paper presents an overview of visualization of Statistics Korea and the Bank of Korea. It also discusses a future direction to explore the visualization of Korean economic statistics.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.13-38
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• 2024

As economic uncertainties have increased recently due to COVID-19, there is a growing need to quickly grasp private consumption trends that directly reflect the economic situation of private economic entities. This study proposes a method of estimating private consumption in real-time by comprehensively utilizing big data as well as existing macroeconomic indicators. In particular, it is intended to improve the accuracy of private consumption estimation by comparing and analyzing various machine learning methods that are capable of fitting ultra-high-dimensional big data. As a result of the empirical analysis, it has been demonstrated that when the number of covariates including big data is large, variables can be selected in advance and used for model fit to improve private consumption prediction performance. In addition, as the inclusion of big data greatly improves the predictive performance of private consumption after COVID-19, the benefit of big data that reflects new information in a timely manner has been shown to increase when economic uncertainty is high.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.270-278
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• 2014

The stability and security management of IT data becomes more important because information security threats increases rapidly in Big Data era. The operational policy of the data backup considering information security threats is required because the backup policy is the fundamental method that prevents the damage of security threats. We present an economic approach for a data backup system with information security threats which damage the system. The backup operation consists of the differential backup and the batch backup. We present a stochastic model considering the occurrence of information security threats and their damage. We analyze the stochastic model to derive the performance measures for the cost analysis. Finally we analyze the average cost of the system and give numerical examples.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.86.2-86.2
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• 2010

태양광발전 시스템에 있어 일사량의 높고 낮음은 경제성 평가를 결정하는 주요인자로 작용하며 일사량은 지역적, 지형적 환경 조건의 차이에 따라 달리 나타난다. 본 연구에서는 주암 저수지 수면에 설치된 수면태양광 일사량 계측자료와 지상에서의 주암댐 관리단 옥상에 설치된 일사량 계측자료를 비교하여 분석한 결과 수면태양광의 일사량이 지상에서의 일사량 보다 약간 상회하는 패턴을 보이며 풍속, 기온 등 기타 데이터 분석 시 수면이 태양광발전에 있어 지상보다 더 유리하다는 점을 검증 할 수 있었다. 또한 취득한 데이터를 가지고 경제성 분석 프로그램을 사용하여 분석한 결과 지상보다 수면태양광이 더 경제성 있다는 결과를 얻을 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.394-395
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• 2023

"이성적이며 이상적인 합리적 인간"을 가정하는 기존 경제학의 이론이 항상 실제 상황과 일치하지는 않는 것으로 알려져 있다. 이의 대안으로 나온 행동경제학은, 인간의 경제적 의사결정에 심리, 인지, 감정, 사회문화적 배경 등이 영향을 미친다고 본다. 본 연구에서는 행동경제학에 의거하여, 개인의 감정과 경험이 경제적 의사결정에 영향을 미치는지 여부를 빅데이터 모델을 활용하여 분석하였다. SNS 여론으로는 Reddit, 주가지수로는 S&P 500 을 선정하였다. 수집한 텍스트 데이터를 전처리와 감정분석을 통해 독립변수 값으로 사용했고, 주가지수 등락의 방향성을 종속변수로 사용하여 로지스틱 모형을 구성했다. 모델을 활용하여 분석한 결과 Public sentiment 와 Market sentiment 간 양의 상관관계를 확인할 수 있었다. 또한, lag 를 설정하는 모델이 정확도가 더욱 높음을 확인해, 기존 경제학의 EMH 와 대립되는 바를 확인할 수 있었다. 하지만 최적의 lag 산정을 위해, 더 광범위한 데이터를 바탕으로 한 후속연구가 필요하다.

• The Journal of Bigdata
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• v.6 no.2
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• pp.1-15
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• 2021

The unprecedented pandemic of infectious diseases called COVID-19 has dampened human and material movement, and changes in the global economic structure have caused various economic and industrial problems such as worsening employment along with the domestic and international economic recession. In this crisis situation, the government announced the "New Deal" as a new card to enhance economic vitality following the "emergency disaster support fund." This means that the first business of the Digital New Deal, the beginning and core of the New Deal, begins digital transformation from collecting data, which is the "rice" of digital transformation to the data dam. Until now, not only the government but also local governments have established and operated platforms for collecting and sharing public data by establishing various data portals. It is evaluated that it lacks utilization for commercialization as not only the government but also local governments focus only on building the platform without considering the business model when building the initial public data platforms. In particular, in the case of regions, there is a lack of public data to be used for data business, so it is necessary to utilize data from public institutions in the region. In this study, various data collection, data quality improvement, and data utilization improvement were suggested as measures to solve these problems.