• Title/Summary/Keyword: Data Portal

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An Exploratory Study on Key Attributes of Specialty Coffee by Online Big Data Analysis (온라인 빅 데이터 분석을 활용한 스페셜티 커피 속성에 대한 탐색적 연구)

  • Lim, Miri;Wun, Daiyeol;Ryu, Gihwan
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.3
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    • pp.275-282
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    • 2020
  • Social interest on high-quality specialty coffee is increased due to customers' growing experience upon coffee and recent change of coffee culture, which is taking one step further from putting emphasis on not just price and quality but also psychological satisfaction. As a culture of drinking coffee and giving much value on its taste and flavor, a number of customers increasingly demand coffee which is probable to suit one's taste. Likewise, the number of specialty coffee shops is increasing with growing qualities of their coffee. Therefore, the purpose of this study is to analyze the main attributes of specialty coffee and to build a marketing system for specialty coffee shops. The text mining on domestic web portal sites by online big-data analysis is used to extract components of properties of specialty coffee and analyze the degree of how the elements affect the properties. According to the result of the study, words related to coffee taste, coffee beans and baristas were found to play a central role in the properties of specialty coffee.

A Study on the Management and Services of Web Resources in Policy Research Institutes (정책연구기관의 웹자원 관리와 서비스 제공 방안에 관한 연구)

  • Lee, Myeong-Hee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.27 no.2
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    • pp.171-191
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    • 2016
  • This research was examined to evaluate whether the websites of 6 policy research institutes provide web resources which were collected and provided as information resources, and that they were sure that the web resources had value as policy information by content analysis method. Web resources provided as policy information in policy research institutes were classified into and evaluated by 4 categories. Evaluation had been conducted on 10 items in the 4 categories of content, design, accessibility and meta data. From the result, the information content have been found to be reliable and up-to-date although more thorough description is required. Navigation and the search function in the design category were found to be excellent, but dead links were present in all of the institutions. The accessibility was proven to be great as it was able to access information with only three clicks. However, it has been found that a comprehensive review of the meta data is required in order to improve the accuracy of search functions. In conclusion, improvements to the dead link problems, quality control of the meta data, systematic and professional management plan of policy research information, and the establishment of a comprehensive policy research information portal system have been proposed.

Changes in consumer perception of fashion products in a pandemic - Effects of COVID-19 spead - (팬데믹 상황에서의 패션제품에 대한 소비자의 인식 변화 분석 - 코로나19 확산의 영향 -)

  • Choi, Yeong-Hyeon;Lee, Kyu-Hye
    • The Research Journal of the Costume Culture
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    • v.28 no.3
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    • pp.285-298
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    • 2020
  • This study aimed at examining fashion consumers' awareness during the COVID-19 pandemic. Big data analysis methods, such as text mining, social network analysis, and regression analysis, were applied to user posts about fashion on Korean portal websites and social media during COVID-19. R 3.4.4, UCINET 6, and SPSS 25.0 software were used to analyze the data. The results were as follows. In researching the popular fashion-related topics during COVID-19, the prevention of infection and prophylaxis were significant concerns in the early stage (Jan 1 to Jan 31, 2020), and changed to online channels and online fashion platforms. Then, various topics and fashion keywords appeared with COVID-19-related keywords afterwards. Fashion-related subjects concerned prophylaxis, home life, digital and beauty products, online channels, and fashion consumption. In comparing fashion consumers' awareness during COVID-19 with SARS and MERS, "face masks" was the common keyword for all three illnesses; yet, the prevention of infection was a major consumer concern in fashion-related subjects during COVD-19 only. As COVD-19 cases increased, the search volume for face masks, shoes, and home clothes also increased. Consumer awareness about face masks shifted from blocking yellow dust and micro-dust to the sociocultural significance and short supply. Keywords related to performance turned out to be the major awareness as to shoes, and home clothes were repurposed with an expanded range of use.

Relevant Keyword Collection using Click-log (클릭로그를 이용한 연관키워드 수집)

  • Ahn, Kwang-Mo;Seo, Young-Hoon;Heo, Jeong;Lee, Chung-Hee;Jang, Myung-Gil
    • The KIPS Transactions:PartB
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    • v.19B no.2
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    • pp.149-154
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    • 2012
  • The aim of this paper is to collect relevant keywords from clicklog data including user's keywords and URLs accessed using them. Our main hyphothesis is that two or more different keywords may be relevant if users access same URLs using them. Also, they should have higher relationship when the more same URLs are accessed using them. To validate our idea, we collect relevant keywords from clicklog data which is offered by a portal site. As a result, our experiment shows 89.32% precision when we define answer set to only semantically same words, and 99.03% when we define answer set to broader sense. Our approach has merits that it is independent on language and collects relevant words from real world data.

An Analysis of the 2017 Korean Presidential Election Using Text Mining (텍스트 마이닝을 활용한 2017년 한국 대선 분석)

  • An, Eunhee;An, Jungkook
    • Journal of the Korea Convergence Society
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    • v.11 no.5
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    • pp.199-207
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    • 2020
  • Recently, big data analysis has drawn attention in various fields as it can generate value from large amounts of data and is also used to run political campaigns or predict results. However, existing research had limitations in compiling information about candidates at a high-level by analyzing only specific SNS data. Therefore, this study analyses news trends, topics extraction, sentiment analysis, keyword analysis, comment analysis for the 2017 presidential election of South Korea. The results show that various topics had been generated, and online opinions are extracted for trending keywords of respective candidates. This study also shows that portal news and comments can serve as useful tools for predicting the public's opinion on social issues. This study will This paper advances a building strategic course of action by providing a method of analyzing public opinion across various fields.

Image Analysis and Management Strategy for The National Science Museum Utilizing SNS Big Data Analysis (SNS 빅데이터 분석을 활용한 국립과학관에 대한 이미지 분석과 경영전략 제안)

  • Shin, Seongyeon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.1
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    • pp.81-89
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    • 2020
  • The purpose of this study is to investigate science consumers' perceptions of the National Science Museum and suggest effective management strategies for the museum. Research questions were established and the analyses were conducted to achieve the research goals. The collection and analysis of the data were conducted through a new approach to image analysis that combines qualitative and quantitative methods. First, the image of the concept of science was derived from science consumers (adults, undergraduate and graduate students) through a qualitative research method (group-interviewing), and then text analysis was conducted. Second, quantitative research was conducted through LDA (Latent Dirichlet Allocation)-based topical modeling of 63,987 words extracted from 12,920 titles of blog postings from one of the most heavily-trafficked portal sites in Korea. The results of this study indicate that the perception of science differs according to the characteristics of the respondents. Further, topic-modeling extracted 20 topics from the blog posting titles and the topics were condensed into seven factors. Detailed discussions and managerial implications are provided in the conclusion section.

The change of dental clinic name (치과의원 상호명의 시대적 변화)

  • Yu, Su-Been;Song, Bong-Gyu;Yang, Byoung-Eun
    • The Journal of the Korean dental association
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    • v.56 no.12
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    • pp.658-666
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    • 2018
  • This study analyzes 21,686 dental clinic business names from 1946 to February 2016, where official records exist. The results of this study will be used as a historical data of Korean dental clinic and contribute to the decision of dental clinic name. According to the results of analysis, the first official dental clinic used in Korea was 'Chu' in 1946, 'Minsaeng' and 'Chusaeng' in 1958, and "Won" in 1959. In the 1960s, dentists' family names were often used as dental clinics. In the 1970s, dental clinic names were often used as dentists' family name, 'Jung-ang' and 'Seongsin'. In the 1980s, dental clinic name was used more than other names such as 'Seoul', 'Yonsei', 'Hyundai' and 'Sang-a' along with the dentist's family name. In the 1990s, a dental clinic name was used to refer to the words 'Yeonsei', 'Seoul', 'Hyundai', 'Sang-a', 'Isalang', 'Uli', 'Jeil', 'Bubu' used a lot. In the 2000s, Dental Clinic's name began to use english words such as $^{\circ}{\AE}Good$ Morning','White','Prime 'and adjectives such as 'Haengboghan', 'Ipyeonhan'. The characteristic of the dental clinic name in 2010 is the increase of the business name 'UD'. From 1946 to February 2016, the most commonly used dental clinic name was 'Seoul', 'Uri', 'Isarang', 'Yonsei', 'Hyundai', 'Good Morning' 'Jung-ang', 'UD', 'I', 'Miso'.

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Analysis of Dental Hygienist Job Recognition Using Text Mining

  • Kim, Bo-Ra;Ahn, Eunsuk;Hwang, Soo-Jeong;Jeong, Soon-Jeong;Kim, Sun-Mi;Han, Ji-Hyoung
    • Journal of dental hygiene science
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    • v.21 no.1
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    • pp.70-78
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    • 2021
  • Background: The aim of this study was to analyze the public demand for information about the job of dental hygienists by mining text data collected from the online Q & A section on an Internet portal site. Methods: Text data were collected from inquiries that were posted on the Naver Q & A section from January 2003 to July 2020 using "dental hygienist job recognition," "role recognition," "medical assistance," and "scaling" as search keywords. Text mining techniques were used to identify significant Korean words and their frequency of occurrence. In addition, the association between words was analyzed. Results: A total of 10,753 Korean words related to the job of dental hygienists were extracted from the text data. "Chi-lyo (treatment)," "chigwa (dental clinic)," "ske-illing (scaling)," "itmom (gum)," and "chia (tooth)" were the five most frequently used words. The words were classified into the following areas of job of the dental hygienist: periodontal disease treatment and prevention, medical assistance, patient care and consultation, and others. Among these areas, the number of words related to medical assistance was the largest, with sixty-six association rules found between the words, and "chi-lyo," "chigwa," and "ske-illing" as core words. Conclusion: The public demand for information about the job of dental hygienists was mainly related to "chi-lyo," "chigwa," and "ske-illing" as core words, demonstrating that scaling is recognized by the public as the job of a dental hygienist. However, the high demand for information related to treatment and medical assistance in the context of dental hygienists indicates that the job of dental hygienists is recognized by the public as being more focused on medical assistance than preventive dental care that are provided with job autonomy.

The Differences and Activation of Physical Activity Therapy Program in Urban-Rural Region Before and After COVID-19 - Focused on Gimcheon, Jeongeup, and Pyeongtaek - (코로나19 전후 도농지역 신체활동 치유 프로그램의 차이와 활성화 방안 연구 - 김천, 정읍, 평택 중심으로 -)

  • Park, Sang-Kyun;Tomita, Sigeru;Oh, Yoon-Ji;Kim, Dae-Sik;Lee, Wang-Lok
    • Journal of Korean Society of Rural Planning
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    • v.27 no.4
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    • pp.25-32
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    • 2021
  • This study was to analyze the Physical Activity Therapy Programs (PATPs) in U rban-rural region before and after COVID-19 in order to suggest a way of activating program. The subjects were the 43 PATPs performed in 4 Community Health Centers of Gimcheon, Jeongeup, and Pyeongtaek. The basic data was collected by official documents, expenditure budget, the homepage of the centers, national information disclosure portal, telephone interview, and e-mail with the person in charge of the programs. All the data were classified to the administrative districts, the health-related fitness variables, and the life cycles. The American College Sports Medicine Guidelines were used to evaluate the PATPs. As a results, the number of the PATPs was too small compared to the population of the regions. Also, the PATPs were not considered to the characteristics of participants such as Life-Cycle and regional facilities so on. The organization and management of the PATPs were principally deficient in improving health-related fitness variables. In 2020 as the period of COVID-19 pandemic, the number of programs and participants with face-to-face PATPs was significantlry decreased compared to 2019, while that was increased with non-face-to-face PATPs. In conclusion, PATPs should be increased and operated in accordance with scientific exercise prescription guidelines. Also, the programs should be considered with the proportion and characteristics of Life-Cycle population. Further, the various with non-face-to-face PATPs should be developed and screened with based on scientific data for post-corona virus pandemic. Further, non-face-to-face PATPs programs should include a kind of practical way to promote the individual physical activity.

Building-up and Feasibility Study of Image Dataset of Field Construction Equipments for AI Training (인공지능 학습용 토공 건설장비 영상 데이터셋 구축 및 타당성 검토)

  • Na, Jong Ho;Shin, Hyu Soun;Lee, Jae Kang;Yun, Il Dong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.1
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    • pp.99-107
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    • 2023
  • Recently, the rate of death and safety accidents at construction sites is the highest among all kinds of industries. In order to apply artificial intelligence technology to construction sites, it is essential to secure a dataset which can be used as a basic training data. In this paper, a number of image data were collected through actual construction site, for which major construction equipment objects mainly operated in civil engineering sites were defined. The optimal training dataset construction was completed by annotation process of about 90,000 image dataset. Reliability of the dataset was verified with the mAP of over 90 % in use of YOLO, a representative model in the field of object detection. The construction equipment training dataset built in this study has been released which is currently available on the public data portal of the Ministry of Public Administration and Security. This dataset is expected to be freely used for any application of object detection technology on construction sites especially in the field of construction safety in the future.