• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.151-160
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• 2016

The purpose of this research is to investigate Korean popular attitudes and social perceptions of 'sharing economy' terminology at the current moment from a creative or socio-economic point of view. In Korea, this study discovers and interprets the objective and tangible annual changes and patterns of sociocultural collective intelligence that have taken place over the last five years by applying text mining in the big data analysis approach. By crawling and Googling, this study collected a significant amount of time series web meta-data with regard to the theme of the sharing economy on the world wide web from 2010 to 2014. Consequently, huge amounts of raw data concerning sharing economy are processed into the value-added meaningful 'word clouding' form of graphs or figures by using the function of word clouding with R programming. Till now, the lack of accumulated data or collective intelligence about sharing economy notwithstanding, it is worth nothing that this study carried out preliminary research on conducting a time-series big data analysis from the perspective of knowledge management and processing. Thus, the results of this study can be utilized as fundamental data to help understand the academic and industrial aspects of future sharing economy-related markets or consumer behavior.

• Journal of Korea Technology Innovation Society
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• v.15 no.2
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• pp.345-368
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• 2012

As science and technology are the core engines of economic and social affairs, it is becoming increasingly necessary to explore new promising technologies in order to secure competitiveness in science and technology with a view to helping upgrade the country's overall competitiveness and promoting industrial development. The governments of major advanced countries provide R&D support for promising future technologies. Even in South Korea, a study is being carried out to set up a model for forecasting future technologies and reinforcing the relevant survey system. This study intends to explore methods of identifying promising future technologies in the bio-science sector, which has emerged as a new growth engine. It will use a text-mining technique to collect and analyze theses in the bio science sector. It will identify key research sectors by analyzing thesis contour lines, and then review promising future key research subjects through in-depth study.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.429-429
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• 2023

우리나라의 물 관련 정책 방향이 환경 중심의 수자원 관리에서 친수공간 및 정보의 확보와 같은 안전한 물관리로 확대되면서 정책추진에 기초가 될 수 있는 신뢰도 높은 수문자료의 생산이 보다 중요시되고 있다. 국가 수문조사사업은 이러한 정책기조에 맞춰 제도적인 뒷받침과 함께 조사의 범위와 기술, 품질관리 등의 영역을 넓히며 그 기능을 활발히 하고 있으나, 물관리 정책의 경향에 따른 수문조사사업의 방향성과 특징을 구조적으로 살펴본 연구는 부족한 것으로 파악된다. 따라서 본 연구는 친수·친환경적 물관리가 강조된 시기('97~현재)를 중점으로 하여 물관리 정책과 관련 계획의 변화가 수문조사사업에 어떠한 영향을 주는지 고찰하였다. 이를 위해 물관리 여건의 변화에 따라 달라진 관련 정책별 주제어의 분포와 수문조사사업과 연관된 주요어의 출현빈도 및 경향을 살펴보고, 주요 연관어와 연계한 사업의 방향과 구조를 분석하였다. 분석자료로는 물관리 관련 법령 등의 제도와 언론기사자료, 정책별 추진방향을 활용하였다. 정책의 추진방향은 1) 수자원의 종합적 개발에서 친환경적 측면과 지속가능성이 강조된 수자원장기종합계획(3-1차~4-3차)과 2) 사람과 자연이 함께 고려된 맑고 안전한 물, 통합물관리 등의 전략이 수록된 국가물관리기본계획(1차), 3) 정책의 기조에 따라 수립 및 보완된 수문조사 기본계획(1~2차)을 바탕으로 하였다. R프로그램을 통한 텍스트 마이닝을 활용하여 각 자료에서의 주제어 분포와 출현빈도를 분석하고, 정책별 추진방향과 수문조사사업의 연계성을 나타내었다. 연구의 함의를 담은 결과로서 물관리 여건이 변화된 시점별 주요연관어를 중심으로 한 정책동향과 수문조사사업의 특징 및 방향을 요약·비교하여 제시하였으며, 이는 물관리 분야에서의 국정운영 목표와 연계하여 국가 수문조사사업의 사업성을 고찰하는 연구의 기반이 될 수 있으리라 생각된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.93-96
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• 2018

Big datatics technology that can store and analyze data and obtain new knowledge has been adjusted for importance in many fields of the society. Big data is emerging as an important problem in the field of information and communication technology, but the mind of continuous technology is rising. R, a tool that can analyze big data, is a language and environment that enables information analysis of statistical bases. In this thesis, we use this to analyze the Bible data. R is used to investigate the frequency of what text is distributed and analyze the Bible through analysis of social network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1199-1205
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• 2021

In the era of big data, not only structured data well organized in databases, but also the Internet, social network services, it is very important to effectively analyze unstructured big data such as web documents, e-mails, and social data generated in real time in mobile environment. Big data analysis is the process of creating new value by discovering meaningful new correlations, patterns, and trends in big data stored in data storage. We intend to summarize and visualize the analysis results through frequency analysis of unstructured article data using R language, a big data analysis tool. The data used in this study was analyzed for total 104 papers in the Mon-May 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 1,538 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.151-154
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• 2021

Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.326-327
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• 2021

Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Journal of Korean Home Economics Education Association
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• v.30 no.3
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• pp.111-127
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• 2018

The purpose of this study was to analysis the home economics education curriculum from the first national curriculum to the 2015 revised curriculum using text mining techniques used in big data analysis. The subjects of the analysis were 10 curriculum texts from the first national curriculum to the 2015 revised curriculum via the National Curriculum Information Center. The major findings of this study were as follows; First, the number of data from the 4th curriculum to the 2015 revised curriculum gradually increased. Second, as a result of extracting core concept of the curriculum, there were core concept words that were changed and maintained according to the curriculum. 'Life' and 'home' were core concepts that persisted regardless of changes in the curriculum, after the 2007 revised curriculum, 'problem', 'ability', 'solution' and 'practice' were emphasized. Third, through core concept network analysis for each curriculum, the relationship between core concepts is represented by nodes and lines in each home economics curriculum. As a result, it was confirmed that the core concepts emphasized by the times are strongly connected with 'life' and 'home'. Based on these results, this study is meaningful in that it provides basic data to form the identity and the existing direction of home economics education.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.41-47
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• 2022

In this paper, we propose how to implement text summaries for colloquial data that are not clearly organized. For this study, SAMSum data, which is colloquial data, was used, and the BERTSumExtAbs model proposed in the previous study of the automatic summary model was applied. More than 70% of the SAMSum dataset consists of conversations between two people, and the remaining 30% consists of conversations between three or more people. As a result, by applying the automatic text summarization model to colloquial data, a result of 42.43 or higher was derived in the ROUGE Score R-1. In addition, a high score of 45.81 was derived by fine-tuning the BERTSum model, which was previously proposed as a text summarization model. Through this study, the performance of colloquial generation summary has been proven, and it is hoped that the computer will understand human natural language as it is and be used as basic data to solve various tasks.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.533-542
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• 2011

Visualization elements as the technology to offer information to users effectively have become more important. In this study, we evaluate the usefulness of visualization elements in InSciTe which is a technology intelligence service developed by using Semantic Web technologies and text mining technologies for establishing R&D strategy using papers and patents. We propose design which can be preferred by users and applying methods of visualization elements through the quantitative and qualitative evaluation about each types of service. As a result of evaluation, we conclude that the visualization elements in InSciTe are implemented user-friendly to improve user's cognitive intuition.