• The Journal of Industrial Distribution & Business
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• v.12 no.8
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• pp.21-32
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• 2021

Purpose: With the advent of the era of the 4th industrial revolution, called a new technological revolution, the necessity of fostering future talents equipped with AI utilization capabilities is emerging. However, there is a lack of research on AI education design and competency-based education curriculum as education for business major. The purpose of this study is to design AI education to cultivate competency-oriented AI literacy for business major in universities. Research design, data and methodology: For the design of AI basic education in business major, three expert Delphi surveys were conducted, and a demand analysis and specialization strategy were established, and the reliability of the derived design contents was verified by reflecting the results. Results: As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived from this were data structure understanding and processing, visualization, web scraping, web crawling, public data utilization, and concept of machine learning and application. Conclusions: The educational design content derived through this study is expected to help establish the direction of competency-centered AI education in the future and increase the necessity and value of AI education by utilizing it based on the major field.

• International Journal of Advanced Culture Technology
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• v.5 no.4
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• pp.51-56
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• 2017

In every Summer and Winter, there open soccer transfer markets. And these markets draw huge attention from soccer fans and other ordinary people all around world. This phenomenon might indicate great interest of people from the amount of news, blog articles, public messages and replies from online community and forums about popular players and clubs of many leagues. Especially, transfer markets in the year 2017 have generated many gossips than before. In this research, we performed keyword analysis and ranking of news and messages collected and analyzed from online news sites and online forum sites, in order to investigate who and what clubs are mainly discussed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.401-402
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• 2018

최근 다양한 인터넷 쇼핑 서비스가 등장하고 보편화 되었다. 제주도는 국제자유도시로서 관광업에 관련된 서비스 업종이 많이 발달해 있다. 따라서 많은 수의 사업장이 무형상품을 제공하고 있다. 많은 소비자가 인터넷을 통한 구매를 진행하기 때문에 많은 사업장에서 인터넷을 통한 판매를 진행하고 있다. 이 과정에서 많은 사업장에서 오픈 마켓 관리에 어려움을 겪고 있다. 이 문제를 해결하기 위해 무형상품을 위한 오픈 마켓 통합관리 시스템을 구현하였다.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.474-482
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• 2023

Data mining is a technique for extracting valuable information from vast amounts of data by analyzing statistical and mathematical operations, rules, and relationships. In this study, we employed data mining technology to analyze the data concerning the painting poetry of Maehwado (plum blossom paintings) from the early Joseon Dynasty. The data was extracted from the Hanguk Munjip Chonggan (Korean Literary Collections in Classical Chinese) in the Hanguk Gojeon Jonghap database (Korea Classics DB). Using computer information processing techniques, we carried out web scraping and classification of the painting poetry from the Hanguk Munjip Chonggan. Subsequently, we narrowed down our focus to the painting poetry specifically related to Maehwado in the early Joseon Dynasty. Based on this, refined dataset, we conducted an in-depth analysis and interpretation of the text data at the syllable corpus level. As a result, we found a direct correlation between the corpus statistics for each syllable in Maehwado painting poetry and the symbolic meaning of plum blossoms.

• The Korean Journal of Emergency Medical Services
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• v.24 no.1
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• pp.85-92
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• 2020

Purpose: The purpose of this study was to analyze the English abstract key words found within the Korea Society of Emergency Medical Services journal using text mining techniques to determine the adherence of these terms with Medical Subject Headings (MeSH) and identify key word trends. Methods: We analyzed 212 papers that were published from 2012 to 2019. R software, web scraping, and frequency analysis of key words were conducted using R's basic and text mining packages. Additionally, the Word Clouds package was used for visualization. Results: The average number of key words used per study was 3.9. Word cloud visualization revealed that CPR was most prominent in the first half and emergency medical technician was most frequently used during the second half. There were a total of 542 (64.9%) words that exactly matched the MeSH listed words. A total of 293 (35%) key words did not match MeSH listed words. Conclusion: Researchers should obey submission rules. Further, journals should update their respective submission rules. MeSH key words that are frequently cited should be suggested for use.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.74-75
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• 2017

In this paper, we analyzed 3,668 papers of JKIICE from 2007 to 2016 using text mining methods for understanding research fields. We used web scraping programs of Python language for data collection, and utilized topic modeling methods based on LDA algorithm implemented by R language. In the results, we verified that representative research areas of JKIICE could be downsized to 9 areas only by the analysis though the submission areas were 19 areas by 2016.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.787-789
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• 2016

Today, need for a development system that provides the data to a chronic disease, and management has emerged. However, for most of the disease management system provides a wide range of data to the user and problem does not provide for important keyword or data existed. In this paper, analyzing the data for a disease through the R Programing it makes like the most relevant keyword in the illness to the user. This study was a system in which only the important parts when the user to manage their disease can be efficiently managed. By utilizing the proposed system to the user it is considered to be Except for unnecessary data or keyword and to be able to see the data and the keyword in need.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.268-270
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• 2019

In this paper, we analyzed the papers related to the "4th Industry". In order to analyze the papers, total of 685 papers were collected by searching with the keyword "4th industry" in Korea Journal Index(KCI) from 2016 to 2019. We used Python-based web scraping program to collect papers. As a result of analysis, it was confirmed that artificial intelligence, big data, Internet of things(IoT), digital, network and so on have emerged as the major technologies, and it was confirmed that research has been utilizing the major technologies in various fields related to the 4th industry such as industry, government, education field, and job.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.161-167
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• 2021

Laboratory Information Management System(LIMS) is a centralized database for storing, processing, retrieving, and analyzing laboratory data, and refers to a computer system or system specially designed for laboratories performing inspection, analysis, and testing tasks. In particular, LIMS is equipped with a function to support the operation of the laboratory, and it requires workflow management or data tracking support. In this paper, we collect data on websites and various channels using crawling technology, one of the automated big data collection technologies for the operation of the laboratory. Among the collected test methods and contents, useful test methods and contents useful that the tester can utilize are recommended. In addition, we implement a complementary LIMS platform capable of verifying the collection channel by managing the feedback.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2101-2121
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• 2020

The rapid growth of instructional videos repositories and their widespread use as a tool to support education have raised the need of studies to assess the quality of those educational resources and their impact on the quality of learning process that depends on them. Khan Academy (KA) repository is one of the prominent educational videos' repositories. It is famous and widely used by different types of learners, students and teachers. To better understand its characteristics and the impact of such repositories on education, we gathered a huge amount of KA data using its API and different web scraping techniques, then we analyzed them. This paper reports the first quantitative and descriptive analysis of Khan Academy repository (KA repository) of open video lessons. First, we described the structure of repository. Then, we demonstrated some analyses highlighting content-based growth and evolution. Those descriptive analyses spotted the main important findings in KA repository. Finally, we focused on users' interactions with video lessons. Those interactions consisted of questions and answers posted on videos. We developed interaction profiles for those videos based on the number of users' interactions. We conducted regression analysis and statistical tests to mine the relation between those profiles and some quality related proposed metrics. The results of analysis showed that all interaction profiles are highly affected by video length and reuse rate in different subjects. We believe that our study demonstrated in this paper provides valuable information in understanding the logic and the learning mechanism inside learning repositories, which can have major impacts on the education field in general, and particularly on the informal learning process and the instructional design process. This study can be considered as one of the first quantitative studies to shed the light on Khan Academy as an open educational resources (OER) repository. The results presented in this paper are crucial in understanding KA videos repository, its characteristics and its impact on education.