• Korean Medical Education Review
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• v.19 no.3
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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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• v.8 no.8
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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.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.3
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• pp.275-283
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• 2005

Ontologies are the core components of the Semantic Web and knowledge-based systems. But it is difficult to find useful ontologies in actual domains. In order to build useful domain ontology, the conceptualization of the domain knowledge by knowledge experts of the specific domain and the specification of conceptualized knowledge with formal languages by ontology designers are required. In addition, structured and detailed guidelines and methods should be provided to be shared by the development team members. However, existing ontology building methodologies define and describe the skeletal structure of the whole building process at the top-layer. We build a useful academic ontology that is based on the conceptual knowledge structure in the domain of philosophy, and propose a detailed methodology to build a text ontology based on Topic Maps. Our methodology consists of two phases, ontology modelling and ontology implementation. We implement a philosophy knowledge portal to support retrieving and navigating of the philosophy knowledge.