• 의학교육논단
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• 제19권3호
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.

• The Journal of Asian Finance, Economics and Business
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• 제8권8호
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• pp.271-285
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• 2021

The aim of this research was to look into the relationship between leadership; transformational leadership, transactional leadership, and employee innovation, as well as the mediating impact of cultural diversity between leadership and employee innovation. Structured questionnaire was used to collect the data from 633 public and private universities' employees in the United Arab Emirates (UAE) with the help of the stratified sampling technique, and hypothesis verified through structural equations modelling (AMOS-21). Findings of the study shows that leadership has positive impact on employee innovation and cultural diversity partially mediates the relationship between leadership and innovative performance of UAE universities' employees. Practical implication of the study is to understand how universities can enhance their employees' innovation which is crucial for their competitiveness and survival. Moreover, the increasing prevalence of cultural diversity, as work arrangements in universities, raises the question of how to successfully manage employees. Although few studies have looked into how transformational and transactional leadership styles affect employees' innovation performance, this study expands on the topic by concentrating on sub-dimensions of leadership that foster innovation through idea generation and execution at the United Arab Emirates universities. This study offers valuable insights for educational leaders and throws light on the main characteristics of leadership which helps the employees to perform better in terms of innovation.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제11권3호
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• pp.275-283
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• 2005

시맨틱 웹이나 지식기반 시스템에서 지식 검색의 핵심 컴포넌트는 온톨로지이다. 하지만 현재 실용적인 온톨로지가 구축된 경우를 찾아보기는 어렴다. 실용적인 온톨로지 구축을 위해서는 특정 도메인의 지식 전문가에 의한 지식의 개념화와 온톨로지 설계자에 의한 지식의 명세화가 필요하며 이를 바탕으로 개발 팀원들 사이에 공유할 수 있는 자세한 온톨로지 생성 가이드라인이 필요하다. 그러나 기존의 온톨로지 생성 방법론은 은톨로지 구축 프로세스의 단계들을 상위 수준에서 나열하는 절차 중심의 방법론이다 본 논문에서는 철학 학문의 지식을 구조화하는 실용적인 온톨로지를 구축하는 방법으로서 텍스트 내용에 들어있는 지식을 온톨로지로 생성하는 토픽맵 기반의 덱스트 온톨로지 방법론을 제시하였다. 이 방법론은 지식 자원으로부터 지식을 분석하고 추출하는 온톨로지 모델링 단계와 형식 언어와 데이타 모델을 이용하여 온톨로지를 생성하는 온톨로지 구현 단계로 구성된다. 방법론과 함께 본 논문에서는 철학 온톨로지에 기반한 철학 지식 검색의 효율성을 보이기 위해 철학 지식 포털을 구현하였다.