• Journal of Digital Convergence
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• v.17 no.4
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• pp.115-122
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• 2019

In the online marketplace, consumers are exposed to various products and freely express opinions. As consumer product reviews have a important effect on the success of online markets and other consumers, online market needs to accurately analyze the consumers' emotions about their products. Text mining, which is one of the data analysis techniques, can analyze the consumer's reviews on the products and efficiently manage the products. Previous studies have analyzed specific domains and less than 20,000 data, despite the different accuracy of the analysis results depending on the data domain and size. Further, there are few studies on additional factors that can improve the accuracy of analysis. This study analyzed 72,530 review data of food product domain that was not mainly covered in previous studies by using ensemble technique. We also examined the influence of summary review on improving accuracy of analysis. As a result of the study, this study found that Boosting ensemble technique has the highest accuracy of analysis. In addition, the summary review contributed to improving accuracy of the analysis.

• Informatization Policy
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• v.21 no.2
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• pp.3-23
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• 2014

The purpose of this research is to analyze research trend of e-participation in Korea which is highly recognized today. Sixty research papers on e-participation published from 2001 to 2013 are analyzed for this research. Main ideas and contents of each paper are reviewed and research subjects and methods of overall papers are analyzed. Mostly, actual state and promotion of e-participation is studied through the analysis of local government web sites, and other specific subjects on e-participation are also studied. Currently, research on e-participation is rather shrinking, and therefore, it is necessary to suggest valid ways to promote e-participation through research on influencing factors to e-participation and e-participation in central government.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.427-432
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• 2021

현재 한국어 의존 구문 분석의 표준은 어절 단위로 구문 분석을 수행하는 것이다. 그러나 의존 구문 분석의 분석 단위(어절, 형태소)에 대해서는 현재까지 심도 있는 비교 연구가 진행된 바 없다. 본 연구에서는 의존 구문 분석의 분석 단위가 자연어 처리 분야의 성능에 유의미한 영향을 끼침을 실험적으로 규명한다. STEP 2000과 모두의 말뭉치를 기반으로 구축한 형태소 단위 의존 구문 분석 말뭉치를 사용하여, 의존 구문 분석기 모델 및 의존 트리를 입력으로 활용하는 문장 의미 유사도 분석(STS) 및 관계 추출(RE) 모델을 학습하였다. 그 결과, KMDP가 기존 어절 단위 구문 분석과 비교하여 의존 구문 분석기의 성능과 응용 분야(STS, RE)의 성능이 모두 유의미하게 향상됨을 확인하였다. 이로써 형태소 단위 의존 구문 분석이 한국어 문법을 표현하는 능력이 우수하며, 문법과 의미를 연결하는 인터페이스로써 높은 활용 가치가 있음을 입증한다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.77-78
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• 2010

본 연구는 공공기반시설인 소방서 위치의 중요성을 인식하여 서울시의 소방서의 위치를 분석하고 최적의 위치에 있는지 평가하고자 한다. 소방서의 입지분석을 위하여 소방관서의 입지조건이 되는 연구의 밀집도, 건물의 수 자료와 소방방재청에서 분석한 통계자료의 정량적인 분석을 통해서 소방서의 공급량을 결정한다. 결정된 공급량, 즉 소방서 설치 개수에 따라 소방 서비스의 취약지점의 발생을 최소화하기 위하여 네트워크 분석과 입지조건 요소를 이용하여 서비스 수준을 평가한다.

• The Korean Journal of Applied Statistics
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• v.12 no.1
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• pp.97-107
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• 1999

프로파일 분석은 반복측정 자료를 분석하는데 있어서 널리 사용되는 다변량 분석모형이다. 프로파일 분석에서는 처리 그룹간의 비교와 반응 프로파일의 평행성 검정을 위해서 4가지 검정통계량이 널리 사용되고 있다. 이들 검정통계량은 Wilks의 통계량($\Lambda$), Pillai's Trace 통계량(V), Hotelling-Lawley Trace 통계량(U), Roy's Maximum Root 통계량($\Theta$ )이다. 그 동안 이들 통계량들을 비교하기 위한 여러 연구가 있었지만 주로 일반적인 다변량 분산분석 모형에 근거한 비교였다. 본 논문에서는 자료가 반복측정 자료이고 우리의 관심이 프로파일 분석에 있을 때에 이 4가지 통계량의 비교에 초점을 맞추었다.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.321-322
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• 2018

본 연구는 유전체 분석 연구 중에 중요한 어셈블리 및 분석 시스템을 활용하는 데 있어 많은 연구자들이 컴퓨터 지식의 부족으로 인하여 신속한 분석을 수행하지 못하여 연구에 많은 어려움을 겪고 있어 이를 극복하기 위하여 일반 연구자도 쉽게 유전체를 분석할 수 있도록 다양한 분석방법을 자동으로 제공해주는 사용자 관점의 분석 파이프라인을 설계하고 구현하였다.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.4
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• pp.129-146
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• 2020

This study aims to investigate the outcomes and limitations of research studies on records and archives organization published in Korea. In particular, it will serve as an in-depth examination of the contribution of this area of research to the improvements and changes in the country's records management field. To this end, 150 journal articles related to the records and archives organization were gathered. After extracting refined keywords from the titles and author-assigned keywords, terminology analysis and contents analysis were conducted. On the one hand, terminology analysis (frequency and network analysis) identified frequently discussed topics and the relationships between them. On the other hand, through content analysis, the study revealed the detailed contents regarding the two main topics and their meanings.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.151-156
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• 2018

The purpose of this study is to conduct a meta-analysis of 18 papers that can be verified among the papers on the subject of TPM. Five hypotheses were set for the analysis and meta - analysis was carried out with CMA as presented in each research paper. As a result of analysis, I-square value is more than 75% in four hypotheses. Therefore, the null hypothesis that the size of the population effect is the same for all studies was rejected. The reason for the heterogeneity is that the research characteristics such as the distribution of the respondents, the study conditions, the study period, and the study area are different. In this case, a summary statistic of the individual studies that can be classified according to the characteristics of the research is needed to analyze the effect size difference. However, individual studies do not provide a summary statistic that can classify the effect differences, so it is not possible to analyze the causes of heterogeneity.

• 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.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.64-76
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• 2021

Culture technology (CT) becomes important in the recent environment where digital technology drives content-based innovations. However, technological trends of CT have not been systematically discussed. Especially, the trends of CT should be analyzed from the national perspective, because CT has grown with the help of government-driven innovation. Therefore, this paper aims to analyze CT trends focusing on national research projects. We collected data on CT from the national science and technology information service (NTIS) database, analyzed the keyword co-occurrence network, and identified the patterns of technological innovation using a clustering analysis. As a result, we found that CT has contributed to the digital content and cultural media, and has been actively developed with the help of machine learning technique. Especially, due to the rise of Covid-19, the non-face-to-face online content is rapidly increasing. This study provides important clues for understanding, analyzing CT trends.