• Journal of Industrial Convergence
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• v.18 no.1
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• pp.73-78
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• 2020

To analyze the main topics related to the use of blockchain technology, the Topic Modeling Technique was applied to the 'Blockchain Technology Utilization' big data shown in newspaper articles. To this end, from 2013 to 2019, when newspaper articles on the use of blockchain technology first appeared, the topics were extracted from 21 newspapers and analyzed by time to 15,537 articles. As a result of the analysis, articles related to the utilization of blockchain technology have increased exponentially since 2015 and focused on IT_science and economics. Key words related to cryptocurrency, bitcoin and virtual currency were weighted high, although they differed depending on time. Blockchain technology, which had focused on financial transactions, gradually expanded to big data, Internet of Things and artificial intelligence. As a result, changes in corporate topics were also made together to expand into various fields at banks for financial transactions, focusing on large and global companies. The study showed how these topics were changing, along with the main topics in newspaper articles related to the use of blockchain technology.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.107-109
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• 2013

주식 시장에서 거래되고 있는 증권은 MACD(Moving Average Convergence Divergence), Stochastic 등의 보조 지표를 이용하는 기술적 분석을 통하여 매수/매도 시점을 결정한다. 주식 시장의 객관적인 자료를 통하여 분석하는 기술적 분석 방법은 주식 시장 외적인 요소를 반영하는데 있어 한계점이 존재한다. 본 논문에서는 기술적 분석 방법에 기사를 종목별로 분류하고 기사의 긍정 및 부정을 판별하는 문서 분류 기법을 적용하여 주식 외적인 요소를 반영하는 시스템을 제안한다.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.123-141
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• 2007

It has been known that predicting stock price is very difficult due to a large number of known and unknown factors and their interactions, which could influence the stock price. However, we started with a simple assumption that good news about a particular company will likely to influence its stock price to go up and vice versa. This assumption was verified to be correct by manually analyzing how the stock prices change after the relevant news stories were released. This means that we will be able to predict the stock price change to a certain degree if there is a reliable method to classify news stories as either favorable or unfavorable toward the company mentioned in the news. To classify a large number of news stories consistently and rapidly, we developed and evaluated a natural language processing based multi-stage news classification system, which categorizes news stories into either good or bad. The evaluation result was promising as the automatic classification led to better than chance prediction of the stock price change.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.333-349
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• 2015

This study examined the application of the FRBR model to newspapers and news articles. In order to meet the purpose that was mentioned above, we analyzed data items based on the level of newspapers and articles and discussed how the FRBR model may be applied. In terms of the level of a newspaper, each of newspapers, morning/evening paper, issue and edition are regarded as an individual work, and the relationship among them are considered to be the 'whole-part relationship'. Each article on the level of article basis was considered to be a work and was in a relationship of 'whole-part relationship' with the edition of each level of newspapers. Newspaper articles can be represented as texts, photographs, graphics, and tables, etc., and regarded as an individual work. Each work can be a part of the article on a newspaper or can be an independent article itself. Moreover, a uniform heading of each boxed article and running story is included in the work of each article and is forming a 'whole-part relationship'. Because of the changes of the newspaper name, the uniform title of each name regarded as a single binding. It is called the superwork and it is forming 'whole-part relationship' with each name.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.727-730
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• 2003

인터넷의 빠른 보급으로 많은 양의 정보가 유통되기 시작했다. 그러나 사용자들은 필요한 정보들을 취사 선택하기엔 정보들은 양이 너무 방대하다. 각종 사이트에 있는 뉴스들을 실시간으로 사용자들에게 필요한 정보를 제공할 수 있는 뉴스 클리핑은 이러한 사용자들의 요구를 충족할수 있다 하지만 기존의 뉴스 클리핑 시스템은 각 사이트에 접근 후, 수동적인 분석을 통해 뉴스 정보 및 뉴스 기사의 위치를 파악하고 이를 추출하도록 하는 시스템들이다. 본 논문에서 제안하고자 하는 시스템은 사이트의 구조를 파악하고, 뉴스 기사들을 동적으로 추출함으로써 기존 시스템의 단점을 극복하고, 내용 기반의 뉴스기사 검색이 가능하도록 한다.

• 프린팅코리아
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• s.1
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• pp.54-59
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• 2002

본지는 창간을 기념하여 '자격증제도의 문제점과 인력난 해소방안'이라는 주제로 지난 5월 8일 인쇄문화회관 강당에서 인쇄명장 및 인쇄기사 5명을 초청, 좌담회를 개최했다. 유창준편집국장의 사회로 진행된 이날 좌담회에서는 인쇄교육 및 자격증 제도의 문제점과 인력난 원인을 분석해 보고 대안을 모색하는 한편 근로자의 입장에서 인쇄물의 품질향상 방안과 인쇄문화산업 발전방안은 무엇인지에 대해 토론했다. 이날 좌담회에는 인쇄명장 김현, 안형근씨와 인쇄기사 강인술, 김희수, 이민희씨가 참석했다.

• Journal of Platform Technology
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• v.11 no.3
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• pp.83-97
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• 2023

This research aims to identify startup trends by analyzing a large number of news articles through semantic network analysis. Using the BIGKinds article analysis service provided by the Korea Press Foundation, 330,628 news articles from 19 newspapers from January 2013 to December 2022 were comprehensively analyzed. The study focused on exploring the changes in key issues over the past decade, considering the impact of the social environment and global economic trends on entrepreneurship. We compared the number of news articles and changes in issues before and after the COVID-19 pandemic, and visualized entrepreneurship trends through frequency analysis, relationship analysis, and correlation analysis. The results of the study showed that the top keywords for entrepreneurship-related words are startup activation and commercialization, and the correlation between COVID-19 and entrepreneurship keywords is almost negligible in a linear sense, but the number of news articles decreased during the pandemic, which has an impact. In particular, the most frequently mentioned keywords are Ministry of SMEs and Startups, place is the United States, and person is limited. The agency was the SBA, and the entrepreneurship sector is more affected by social issues than any other sector, with the important characteristics of increased frequency of prompt access. This study supplies essential basic data for understanding and exploring issues and events related to entrepreneurship and suggests future research topics in the field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.375-384
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• 2021

This study explored the change in keywords and topics in newspaper articles related to schizophrenia after the Gangnam murder case. The study examined newspaper articles related to schizophrenia for five years before and after the Gangnam murder case. A semantic network analysis was conducted using the NetMiner 4.4.1 program. 610 articles between 2013 and 2018 were retrieved from 8 national newsletters. The most frequent core keyword was 'treatment' before the murder case, but 'incidents' after the case. Four topics were identified: 'becoming chronic if missing the time of treatment due to prejudice', 'being curable with early treatment', 'living an ordinary life with medication', 'being indicted as a murderer while impaired by a mental disorder' before the murder case. After the case, four topics were identified: 'committing murder for delusions, not misogyny', 'medication non-adherence leads to more impulsive behavior', 'claiming leniency for criminals due to the mental impairment', 'killing the police who were mobilized to stop stabbing rampage'. These findings suggest that newspaper articles should provide accurate information about schizophrenia to reduce prejudice and stigma toward patients with schizophrenia and other forms of mental illness.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.111-119
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• 2023

This study aimed to analyze the changes in news articles related to 'Elderly Living Alone' by comparing Big Data-based news articles related to 'Elderly Living Alone' reported before and after the outbreak of COVID-19. For this, 2018 to 2019 were selected before the outbreak of COVID-19, and 2020 to 2021 were selected after the outbreak, and news articles related to 'Elderly Living Alone' were collected and analyzed using BIGKinds. The main results are as follows. First, the number of related articles decreased after the outbreak of COVID-19 compared to before. Second, there was no significant difference in the analysis of related words. Third, in the relationship diagram analysis, 'Executives' before the outbreak of COVID-19 and 'Corona 19' after that showed the most weight. This study is expected to be used as basic data in preparing improvement plans for national policies and systems in the context of the spread of infectious diseases in relation to 'Elderly Living Alone'.

• The Journal of Korean society of community based occupational therapy
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• v.7 no.3
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• pp.35-42
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• 2017

Objective : The purposes of this study are to examine the correlations among work ability and sleep quality in bus driver and to find the factors affecting work ability. Methods : The participants were 120 inpatients with bus driver. The Work Ability Index(WAI) was used for measuring work ability and the Pittsburgh Sleep Quality Index (PSQI) was utilized to measure sleep quality. The relationships among the variables were examined with Pearson correlation coefficients. And the stepwise multiple regression analysis were performed to identify the predictive variables that explain changes of work ability. Results : As a result of analyzing correlation of variables affecting work ability, there was negative correlation in contact sleep quality(p<.001) and working hours(p<.001). Finally, Work ability was identified as a factor that explains 48.2% of change in sleep quality(p<.001) and working hours(p<.01). Conclusion : It was found that intimacy of bus driver was a major variable to affect work ability. The sleep quality and working hours should be considered as a way to improve the bus driver work ability.