• 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.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.35-41
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• 2019

This study aims to analyze the cosmedical cosmetics market and the nature of customer through the social big data analysis. More than 80,000 posts were analyzed using R program. After data cleansing, keyword frequency analysis and association analysis were performed to understand customer needs and competitor positioning, formulated several implications for marketing strategy sophistication and implementation. Analysis results show that "prevention" is a new and essential attribute for appealing target customers. The expansion of the product line for the gift market is also suggested. It has been shown that there is a high correlation with products that can be complementary to each other. In addition to the traditional marketing technique, the social big data analysis based on evidence was useful in deriving the characteristics of the customers and the market that had not been identified before. Word2vec algorithm will be beneficial to find additional.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.122-122
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• 2017

• The Journal of Bigdata
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• v.3 no.1
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• pp.47-54
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• 2018

Previous studies of business process analysis have analyzed various factors such as task, customer service, operator convenience, and execution time prediction. To accurately analyze these factors, it is effective to utilize actual historical data recorded in information systems. Process mining is a technique for analyzing various elements of a business process from event log data. In this case study, process mining was applied to the transaction data of a purchase agency to analyze the business process of their procurement process, the execution time, and the operators.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.111-113
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• 2016

While big data analysis is an useful tool for reading customers' trends, questionnaire survey which directly collects the information of customer trends have been used traditionally in marketing field. In this point, this study attempts to compare the results from two methods such as big data analysis and questionnaire survey on cosmetics product brands.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.89-99
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• 2015

The World Economic Forum and the Korean Ministry of Knowledge Economy have selected big data as one of the top 10 in core information technology. The key of big data is to analyze effectively the properties that do have data. Clustering analysis method of big data techniques is a method of assigning a set of objects into the clusters so that the objects in the same cluster are more similar to each other clusters. Similarity measures being used in the cluster analysis may be classified into various types depending on the nature of the data. In this paper, we studied upper and lower bounds for binary similarity measures with negative matches such as Russel and Rao measure, simple matching measure by Sokal and Michener, Rogers and Tanimoto measure, Sokal and Sneath measure, Hamann measure, and Baroni-Urbani and Buser mesures I, II. And the comparative studies with these measures were shown by real data and simulated experiment.

• Journal of Convergence Society for SMB
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• v.5 no.1
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• pp.1-6
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• 2015

Recently the disease by eating of the modern prevention, management, and trends in the u-healthcare service that provides healthcare services including health promotion is changing rapidly. However, u-healthcare service is a healthcare information that provides users of the disease can not be analyzed even if the service is stored or not stored in the management server status is giving the inconvenience caused to users of the health services. In this paper, we propose a management method of health care services and a big data formation information that provides users of the disease to facilitate the users of health care services through the use magazine big data information regardless of time and place. The proposed method has the user's bio-information and the measured health information and transmits data through a wired or wireless communication to the medical institution and the user's health information data formation by the big user of the analysis of the health information and the disease of the user feedback to the user.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.47-48
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• 2021

사용자 행동 인식(HAR)은 사용자의 행동을 분석하여 사용자의 현재 행동을 추측하는 것이며, 센서 데이터에서 특성을 추출하는 것이 중요하다. 본 연구에서는 다양한 특징 추출 기법을 사용하여 기계학습 모델을 비교한다. 변수마다 특성에 맞는 기법을 사용했으며, 정확도와 Kappa 통계량, F1 score 모두 SVM 모델에서 95.2%, 94.2%, 95.1%로 가장 높았다. 이는 기계학습 모델에서 특징 추출 기법을 사용하여 우수한 정확도를 달성할 수 있음을 보인다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.431-431
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• 2021

4차 산업혁명의 도래로 사회기반시설물의 계획 및 운영관리에 있어 데이터 분석을 통한 가치추출에 대한 관심은 매우 높은 상황이다. 데이터의 가용성과 접근성, 정부 지원 등을 평가하는 공공데이터 개방지수에서 한국은 1점 만점에 0.93점을 획득하여 경제협력개발기구 회원국 중 1위(2019년 기준)를 할 정도로 매우 높은 수준(평균 0.60점)이다. 그러나 공식적으로 발표 및 배포되는 사회기반시설물 관련 정보와 심도 있는 연구 분석이 필요한 정보는 접근이 여전히 제한적이라 할 수 있다. 특히 대표적인 사회기반시설물인 상수도시스템은 대부분 국가중요시설로 지정되어 있어 다양한 정보를 획득하고 분석하는데 제약이 존재하며, 관련 국가통계인 상수도통계에서는 누수사고 등과 같은 비정상적 상황에 대한 사고지점, 원인 등과 같은 세부정보는 제공하고 있지 않다. 본 연구에서는 웹크롤링 및 빅데이터 분석기술을 활용하여 과거 일정기간 발생한 지자체의 상수도 누수사고 관련 뉴스를 전수조사하고 도출된 사고건수를 국가 공인 정보인 상수도통계자료와 비교·분석하였다. 독립적인 누수사고 기사를 추출하기 위해서 중복기사의 제거, 누수 관련 키워드 정립, 상수도분야 이외의 관련기사 제거 등의 절차가 필요하며, 이와 같은 기법은 R프로그래밍을 통해 구현되었다. 추가적으로 뉴스기사의 자연어 처리기반 정보추출기법을 통해 누수사고 건수 뿐만 아니라 사고발생일, 위치, 원인, 피해정도, 그리고 대상 관로의 크기 등을 획득하여 상수도 통계에서 제시하고 있는 정보보다 많은 가치를 추출하여 연계할 수 있는 방안을 제시하였다. 제시된 방법론을 국내 A광역시에 적용하여 누수사고 건수를 비교한 결과 상수도통계에서 제시하고 있는 누수발생건수와 유사한 규모의 사고건수를 뉴스기사분석을 통해 도출할 수 있었다. 제안된 방법론은 추가적인 정보의 추출이 가능하다는 점에서 향후 활용성이 높을 것으로 기대된다.

• The Journal of Sustainable Design and Educational Environment Research
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• v.18 no.2
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• pp.1-11
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• 2019

The purpose of this study is to make objective decisions in the use of closed schools through the development of utilization indicators for the efficient use of closed schools, which is expected to increase continuously. The research phase was largely carried out by drawing preliminary indicators for use in closed schools, drawing final indicators using big data, and quantifying indicators, and finally objectifying them through quantification. The institution intends to apply and verify the facility based on future indicators. This study has implications for the application of big data analysis methods that have not been attempted in planning and research for the use of closed school facilities to date.