• Korean small business review
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• v.42 no.4
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• pp.235-250
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• 2020

This study surveyed the perception of university students about employment in Small and Medium-sized Enterprises(SME) in the Chungbuk area to prepare improvement measures. In particular, the data were collected in descriptive questions along with the existing survey methods, and the perception of SME and decent work was identified using text-mining. As a result of the analysis, there are positive perceptions of jobs at SME such as various work experiences and low job competition rates, while there are generally many negative perceptions in pay, work and welfare. However, as a result of co-occurrence network analysis of responses to decent jobs, 'Information' was derived as a keyword. Currently, college students' negative perception of SME is affected by the lack of sufficient information, which needs to be improved first. To solve this problem, it was proposed to establish and operate a platform that can provide information on employment of SME and select necessary personnel.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.195-201
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• 2018

Smartphones and PCs have become essential components of our daily life. People are expressing their opinions freely in SNS by using these devices. We are able to predict public opinions on specific subject by analyzing the related big data in SNS. In this paper, we have collected opinion data in SNS and analyzed reputation by text mining in order to make a prediction for the will of the people before 19th presidential election in South Korea. The result shows that our method makes more accurate estimate than other election polls.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.405-412
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• 2019

SOLAS requires that ECDIS be installed on ships of more than 500 gross tonnage engaged in international navigation until the first inspection arriving after July 1, 2018. Several accidents related to the use of ECDIS have occurred with its installation as a new major navigation instrument. The 12 incident reports issued by MAIB, BSU, BEAmer, DMAIB, and DSB were analyzed, and the cause of accident was determined to be related to the operation of the navigator and the ECDIS system. The text was analyzed using the R-program to quantitatively analyze words related to the cause of the accident. We used text mining techniques such as Wordcloud, Wordnetwork and Wordweight to represent the importance of words according to their frequency of derivation. Wordcloud uses the N-gram model as a way of expressing the frequency of used words in cloud form. As a result of the uni-gram analysis of the N-gram model, ECDIS words were obtained the most, and the bi-gram analysis results showed that the word "Safety Contour" was used most frequently. Based on the bi-gram analysis, the causative words are classified into the officer and the ECDIS system, and the related words are represented by Wordnetwork. Finally, the related words with the of icer and the ECDIS system were composed of word corpus, and Wordweight was applied to analyze the change in corpus frequency by year. As a result of analyzing the tendency of corpus variation with the trend line graph, more recently, the corpus of the officer has decreased, and conversely, the corpus of the ECDIS system is gradually increasing.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.101-106
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• 2016

A number of non-structured data associated with lectures in the field of university education have been generated and it is an important consideration of the students's written comments lecture evaluation. The purpose of this study is to find student interaction factors associated with the student evaluation of teaching at universities, and to provide some insights into improving the student evaluation program based on the results. So, this study consists of three steps that create interaction score, collect student's written comments satisfaction, and analyze an individual professor score. There are a number of limitations to this study. The limitation is that the study was conducted on a narrow sample of the overall student population.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.66-67
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• 2023

최근 들어, 현대사회는 예측이 불가능한 다양한 위험성들이 존재하여 글로벌 의존도가 높은 항만물류산업의 위험부담이 증가하고 있다. 이에 본 연구에서는 항만산업의 안전성에 영향을 미치는 요인을 알아보기 위해 과거부터 현재까지 국내 항만 안전성에 영향을 미친 이슈들을 시계열적으로 살펴보고자 하였다. 이를 위하여 국내를 대표하는 부산항의 항만 안전성과 관련된 뉴스 기사 텍스트 데이터를 활용하여 LDA 토픽모델링 분석을 진행하여 부산항 항만안전 주요 이슈들의 동향을 살펴보고자 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.277-280
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• 2018

최근 서울시에서는 '미세먼지 비상저감조치'로 '대중교통 무료' 정책을 시행하고 후속 조치로 '시민 참여형 차량 2 부제'를 제안하였다. 본 논문에서는 먼저, 위 두 교통 정책의 실효성을 파악하기 위해 '교통'을 중심으로 각 산업이 미세먼지에 미치는 영향을 알아보고, 위 정책들에 대한 시민들의 반응을 분석한다. 각 산업이 미세먼지에 미치는 영향은 회귀분석으로, 두 정책에 대한 시민들의 반응은 텍스트 마이닝 기법을 통해 알아보았다. 그 결과, 교통수단의 도로 이용 여부에 따라 미세먼지에 미치는 영향력의 정도와 방향이 다름을 알 수 있었고 정책에 대한 관심과 부정적인 의견이 크게 증가함을 알 수 있었다. 또 국외 요인에 대한 해결책도 필요로 함을 알 수 있었다. 마지막으로 위 결과를 토대로 향후 미세먼지 문제와 관련된 정책이 나아갈 방향을 제시한다.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.115-128
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• 2022

The purpose of this study is to conduct keyword trend analysis using articles data on the impact of Covid-19 in the aviation in dustry. In this study, related articles were extracted centering on the keyword "Airline" by dividing the period of 6months before and after Covid-19 occurrence. After that, Topic modeling(LDA) was performed. Through this, The main topic was extracted in the event of an epidemic such as Covid-19, It is expected to be used as primary data to predict the aviation industry's impact when occurrence like Covid-19.

• Journal of Advanced Technology Convergence
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• v.2 no.3
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• pp.1-7
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• 2023

The problem of climate change is intensifying around the world, and the increasing use of fossil fuels is causing a variety of problems. In particular, interest in renewable energy is increasing due to the acceleration of carbon neutrality policies. In this study, we utilized SCOPUS DB to identify trends in renewable energy research. We obtained 1,353 data for which abstracts were available and performed data preprocessing to analyze them. Topic modeling analysis showed that renewable and energy were the most important keywords. In addition, electricity, solar, wind, etc. were analyzed as important keywords. Through the results of this study, it is expected that practitioners of renewable energy-related companies can utilize the research trends related to renewable energy in practice.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.427-428
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• 2021

정보통신기술의 발달로 전자상거래의 증가와 소비자들의 제품에 대한 경험과 지식의 공유가 활발하게 진행됨에 따라 소비자는 제품을 구매하기 위한 자료수집, 활용을 진행하고 있다. 따라서 기업은 다양한 기능들을 반영한 제품이 치열하게 경쟁하고 있는 현 시장에서 우위를 점하고자 소비자 리뷰를 분석하여 소비자의 정확한 소비자의 요구사항을 분석하여 제품기획 프로세스에 반영하고자 텍스트마이닝(Text Mining) 기술과 딥러닝(Deep Learning) 기술을 통한 연구가 이루어지고 있다. 본 논문의 기초자료가 되는 데이터셋은 포털사이트의 구매사이트와 오픈마켓 사이트의 소비자 리뷰를 웹크롤링하고 자연어처리하여 진행한다. 감성분석은 딥러닝기술 중 CNN(Convolutional Neural Network), LSTM(Long Short Term Memory) 조합의 모델을 구현한다. 이는 딥러닝을 이용한 제품기획 프로세스로 소비자 요구사항 반영, 경제적인 측면, 제품기획 시간단축 등 긍정적인 영향을 미칠 것으로 기대한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.219-222
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• 2020

웹툰 시장의 성장에 따라, 웹툰을 주제로 다양한 연구가 진행되고 있다. 그러나 웹툰의 댓글을 분석한 연구는 특정 웹툰에 한정된 연구가 많아 일반적인 웹툰 독자의 댓글 특징을 보기에는 한계가 있다. 또한 웹툰의 흥행과 관련하여, 흥행에 성공한 웹툰과 그렇지 못한 웹툰의 독자 반응을 파악하는 연구는 부족한 실정이다. 따라서 본 연구는 웹툰의 흥행에 주목하여, 흥행의 지표를 웹툰 플랫폼 정식연재로 판단하고, 정식연재가 된 웹툰과 되지 못한 웹툰의 댓글을 비교 분석하였다. 분석 결과, 정식연재가 된 웹툰은 긍정적인 감상평 외에 2차적 저작물을 언급하고 등장인물의 이름 언급이 높았으나 정식연재가 되지 못한 웹툰은 부정적인 감상평 외에, 웹툰 요소에 대한 부정적 언급과 웹툰 장르와 다른 장르의 언급이 나타나 웹툰에 대한 독자의 불만족 요인을 파악할 수 있었다.