• Annual Conference of KIPS
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• 2017.11a
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• pp.174-176
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• 2017

매년 여행을 즐기는 여행객들의 수가 꾸준히 증가하고 있으며, 이러한 추세는 해외여행 뿐 아니라 국내 여행에서도 나타나고 있다. 국내 여행을 즐기는 여행객 수의 증가는 매우 다양하고 복합적인 요인들에 의해 이루어지고 있는 것이 사실이나, 국내 여행객들의 절대 다수는 해외여행과는 달리 패키지 형태 보다는 자유여행 형태의 여행을 선호하고 있다. 이는 해외 여행지 대비 국내 여행지가 여행객들이 취득 및 분석할 수 있는 정보의 접근성이 훨씬 높고 정보의 양 역시 풍부하다는 것에서 기인한다고 할 수 있다. 그러나 이러한 정보 접근의 용이성 및 정보량의 풍요성은 오히려 자유여행을 즐기고자 하는 여행객들이 여행코스 및 숙소를 정하는데 많은 시간을 투자하게 되는 요인으로 작용하고 있다. 때문에 이러한 단점을 해결하고자 본 논문에서 제안하는 애플리케이션은 국내 여행객들이 편리하고 손쉽게 국내 여행을 즐길 수 있도록 여행코스 및 숙소를 지정할 수 있는 기능을 제공한다. 이를 위해, 제안하는 애플리케이션에서는 국내 여행과 관련된 다양한 정보들을 각종 포털 사이트와 SNS에서 수집하고, 이를 기반으로 사용자 선호 정보와의 매칭을 통해 맞춤형 여행 코스 제안 및 숙소 예약 기능을 제공한다. 이를 통해, 국내 여행을 즐기는 여행객들에게 편리함을 제공하고, 국내 여행객 수의 증가를 기대할 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.53-57
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• 2010

현재 많은 포털 사이트에서는 인기가 있거나 중요도가 높은 키워드에 대해 정보를 제공해주는 태그 클라우드나 연관 검색어 등의 기능이 제공되고 있다. 하지만 대부분의 뉴스기사 페이지들은 날짜와 분야별로 기사들이 나열되어 있으며 사용자는 카테고리별로 나누어진 기사를 읽을 수만 있을 뿐 그 기사와 연관된 다른 기사의 정보에 대해서 한눈에 알아 볼 수 있는 방법은 미흡한 실정이다. 또한 연관 검색어 서비스도 사용자가 검색한 입력 내용을 기반으로 연관성 정도를 분석하여 객관성을 보장하지 못하고 있다. 본 논문에서는 기존의 태그 클라우드 방식에서 좀 더 나아가 축적된 뉴스 기사로 부터 검색 키워드와 밀접히 연관된 키워드를 추출하여 제공하는 기사 검색 시스템을 소개한다. 이 시스템은 사용자가 기사 검색을 하였을 때, 키워드와 가장 밀접한 기사를 검색해 주는 것뿐만 아니라 검색어와 관련된 연관 키워드들을 보여주고 연관된 키워드간의 관계성을 보여줌으로써 뉴스 기사들 속에 숨겨진 연관정보의 탐색을 가능하게 한다.

• The Korean Journal of Health Service Management
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• v.13 no.1
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• pp.55-65
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• 2019

Objectives: The purpose of this study is to analyze basic data on socio - demographic characteristics, occupational careers, and desire for employment of job seekers in their Fifties and Sixties using a portal site. Methods: For this research, secondary data were collected by the researcher from 704 job seekers and were statistically analyzed using the SPSS package. Results: The results of the analysis are as follows: Most job seekers want a job that suits their competence and career trajectory, but the reality is that as their age increases, jobs suitable for those in their fifties and sixties are hard to find; thus these job seekers accept simple labor or functional jobs. Conclusions: Differences were found in work conditions such as occupation level, job position, total career years, desired employment type, and expected salary depending on socio - demographic variables. Consequently, improvements should be made for various job searching paths for older adults as well as increasing the accessibility of job searching information.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.2
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• pp.85-108
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• 2018

This study aimed to analyze media reports of the Comprehensive Library Advancement Plan using big data analysis in order to determine trends and implications by period. To do so, related data from 2009 to 2017 were collected from major domestic web portal sites. Words in the collected data were refined through the text mining process and frequency, centrality, and structural equivalence analyses were performed. Results confirmed that, during the implementation of the first and the second phases of the Comprehensive Library Advancement Plan, the focus of the library policy changed from external growth to strengthening internal stability and advancement of library operation, and the media coverage were limited to specific policies such as expansion of library facilities. Findings from this study will serve as useful material for ascertaining the approach to perceive and understand the national library policy represented by the Comprehensive Library Advancement Plan.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.875-885
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• 2018

This study analyzed the major issues of the Candlelight Rally and Taegukgi Rally registered in news comments of the politics section of the portal site from October 24, 2016 to March 19, 2017. We examined the political recognition of the two rallies with the Named Entity Recognition. The main analytical items are the responsibility for impeachment, the subject and method of settlement, and other major issues. As a result of the analysis, the comments of the Candlelight Rally focused on the impeachment support and the legal penalties of the regime ministers, and insisted on resolving the political situation through the next election after impeachment. The comments of the Taegukgi Rally focused on the rejection of the impeachment to maintain the regime and insisted on rejecting the impeachment of the Constitutional Court. The conflicts between the group that supported Candlelight Rallis and the group that supported Taegukgi rallies are predicted to last at least for the time being (Park Geun-hye's trial period) after the presidential election. After the impeachment of the President and replacement of the regime this conflict will develop into the confrontation between the pursuit of liquidation and new politics and the attempt to influence the trial of Park Geun-hye. Therefore, the efforts to integrate society in the aftermath are necessary.

• The Journal of Bigdata
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• v.7 no.2
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• pp.235-244
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• 2022

The rental history data of public bicycles in Seoul were analyzed to examine how pandemic phenomena such as COVID-19 caused changes in people's micro mobility. Data for 2019 and 2021 were compared and analyzed by dividing them before and after COVID-19. Data were collected from public data portal sites, and data marts were created for in-depth analysis. In order to compare the changes in the two periods, the riding direction type dimension and the rental station type dimension were added, and the derived variables (rotation rate per unit, riding speed) were newly created. There is no significant difference in the average rental time before and after COVID-19, but the average rental distance and average usage speed decreased. Even in the mobility of Ttareungi, you can see the slow rhythm of daily life. On weekdays, the usage rate was the highest during commuting hours even before COVID-19, but it increased rapidly after COVID-19. It can be interpreted that people who are concerned about infection prefer Ttareungi to village buses as a means of micro-mobility. The results of data mart-based visualization and analysis proposed in this study will be able to provide insight into public bicycle operation and policy development. In future studies, it is necessary to combine SNS data such as Twitter and Instagram with public bicycle rental history data. It is expected that the value of related research can be improved by examining the behavior of bike users in various places.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.443-454
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• 2017

A positive destination image has an impact on the tourist arrivals and economic growth of the tourist destination. Recently, the content generated by sharing tourist experiences and destination information on the internet has been increasing. The online content has the potential to become a major tourist decision source and provide more in-depth materials and richer content to extract destination image, insight and tourist's perceptions of the destination. This study was designed to explore the destination image of Daegu online and draw lessons for successful image management in an era of big data. Text mining approach and social network analysis were conducted to extract destination image determining elements and assess the influence of the elements. The result showed that destination image elements related to tourist infra-structures and culture, history and art affected the overall destination image of Daegu. Destination marketers should make an effort to grasp these precise destination image and seek ways to boost competitiveness as a tourist destination.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.39-47
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• 2021

This study was conducted to propose a product planning prediction model using logistic regression algorithm to predict seasonal factors and rapidly changing product trends. First, we collected unstructured data of consumers in portal sites and online markets using web crawling, and analyzed meaningful information about products through preprocessing for transformation of standardized data. The datasets of 11,200 were analyzed by Logistic Regression to analyze consumer satisfaction, frequency analysis, and advantages and disadvantages of products. The result of analysis showed that the satisfaction of consumers was 92% and the defective issues of products were confirmed through frequency analysis. The results of analysis on the use satisfaction, system efficiency, and system effectiveness items of the developed product planning prediction program showed that the satisfaction was high. Defective issues are very meaningful data in that they provide information necessary for quickly recognizing the current problem of products and establishing improvement strategies.

• The Korean Journal of Pesticide Science
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• v.15 no.4
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• pp.434-440
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• 2011

In order to establish the guidance of management and safe use hazard substance, trend analysis of hazard substance in/on agricultural products reported by press for 5 years (2005-2009) was performed. Data for the analysis collected from the articles about hazard substances from web portals, newspapers and so on. The mostly detected harmful factors in/on agricultural products were pesticides residue and heavy metals by the reports by press for last 5 years. The number of detected pesticides was slightly increased from 14 to 34 through the passage of time but the number of cases reported by press was not increased. On the other hand, the number of accidents and reports related to heavy metals were highly increased from 3 to 13 and 42 to 112, respectively. 65 pesticides including chlorpyrifos were detected in domestic agricultural products for the 5 years. Frequently detected pesticides were chlorpyrifos, endosulfan, carbendazim, azoxystrobin, and procymidone. Pesticide residues were repeatedly detected on green vegetables such as a green perilla leaf, a lettuce, a leek, and spinach among crops.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.237-245
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• 2022

This study examines the social discourse on the characteristics of the learning community in the untact era, and discusses the directions that learning communities for children could explore and consider in the pandemic situation and beyond. For this purpose, big data for one year, from January 20, 2020 to January 20, 2021, were collected through internet portal sites (includingincluding Google News, Daum, Naver and other News surfaces), using two keywords "untact" and "learning community", and analyzed by employing a word frequency and network analysis method. The analysis results show that several important terms, such as 'village education community', 'operation', 'activity', 'corona 19', 'support', and 'online' are closely related to the learning community in the untact era. The findings from this study also have implications for developing the learning community as an alternative model to fill the existing gaps in public care and education for children during the prolonged pandemic and afterwards. In conclusion, the study findings highlight that it is meaningful to identify key terms and concepts through word frequency analysis in order to examine social trends and issues related to the learning community.