• Knowledge Management Research
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• v.20 no.1
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• pp.77-99
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• 2019

This study aims to examine validity and reliability of the convergence talent measurement. Based on the comprehensive literature review on convergence and convergence talent, we draw 4 main competencies (convergence cognitive, accomplishment, problem solving, and attitude) and 10 critical aspects (creative thinking, critical thinking, cooperation, communication, problem-solving, knowledge accessibility, resource utilization, trust, openness, caring) for building an effective convergence-oriented organization. A validity and reliability test survey were conducted for the analysis to investigate the convergence talent scale. With a data of 151 employees in diverse companies, the results show that the factors demonstrated acceptable levels of validity and reliability. The empirical evidences of our study are 10 key aspects comprising four main dimensions which suggest an available scale for measuring the convergent talent for enhancing convergence-oriented organizations. Our research contributes to the expansion of academic and practical implications on convergence, especially in convergence-oriented organizations.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.749-756
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• 2019

Big data is structured and unstructured data that is so difficult to collect, store, and so on due to the huge amount of data. Many institutions, including universities, are building student convergence systems to foster talents for data science and AI convergence, but there is an absolute lack of research on what kind of education is needed and what kind of education is required for students. Therefore, in this paper, after conducting the correlation analysis based on the questionnaire on basic surveys and courses to improve the curriculum by grasping the satisfaction and demands of the participants in the "2019 Big Data Youth Talent Training Course" held at K University, Regression analysis was performed. As a result of the study, the higher the satisfaction level, the satisfaction with class or job connection, and the self-development, the more positive the evaluation of program efficiency.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.1-7
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• 2023

Since the first outbreak of COVID-19 in 2019, it has caused a huge blow to the restaurant industry. However, as social distancing was lifted as of April 2022, the restaurant industry gradually recovered, and as a result, interest in restaurant start-ups increased. Therefore, in this paper, big data analysis was conducted by selecting "restaurant start-up" as a key keyword through social media big data analysis using Textom and then conducting word frequency and CONCOR analysis. The collection period of keywords was selected from May 1, 2022 to May 23, 2023, after the lifting of social distancing due to COVID-19, and based on the analysis, the development of a restaurant start-up consulting chatbot service is proposed.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.189-202
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• 2023

In the era marked by information inundation, social network analysis is the most important part of big data analysis, with clique detection being a key technology in social network mining. Also, detecting maximal balance clique in signed networks with positive and negative relationships is essential. In this paper, we present two algorithms. The first one is an algorithm, MCDA1, that detects the maximal balance clique using the improved three-way concept lattice algorithm and object-induced three-way concept lattice (OE-concept). The second one is an improved formal concept analysis algorithm, MCDA2, that improves the efficiency of memory. Additionally, we tested the execution time of our proposed method with four real-world datasets.

• ETRI Journal
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• v.34 no.3
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• pp.439-449
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• 2012

In recent innovation trends, one notable feature is the merging and overlapping of technologies: in other words, technological convergence. A key technological convergence is the fusion of biotechnology (BT) and information technology (IT). Major IT advances have led to innovative devices that allow us to advance BT. However, the lack of data on IT-BT convergence is a major impediment: relatively little research has analyzed the inter-disciplinary relationship of different industries. We propose a systematic approach to analyzing the technological convergence of BT and IT. Patent analysis, including citation and co-classification analyses, was adopted as a main method to measure the convergence intensity and coverage, and two portfolio matrices were developed to manage the technological convergence. The contribution of this paper is that it provides practical evidences for IT-BT convergence, based on quantitative data and systematic processes. This has managerial implications for each sector of IT and BT.

• Journal of Technology Innovation
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• v.26 no.3
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• pp.1-36
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• 2018

In the era of the 4th Industrial Revolution, it is important for companies to understand the changing environment by converging various technologies and to respond to the changing business environment. In this study, we conducted a social network analysis on 10 firms in the automotive industry, which have recently been accelerating their competition for technology development, by extracting convergence patents co-classified in two or more of the US registered patents in the last 6 years. As a result, it has been confirmed that the number of technology related to the convergence of the automotive field is greatly increasing, and the convergence between the technologies is becoming stronger. In addition, Volkswagen, Ford and Hyundai showed significant changes in technology convergence. They were analyzed as having a change in strategy in eco-friendly automotive technologies. This study suggests various ways for companies to utilize the results of network analysis more meaningfully.

• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.122-130
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• 2020

The purpose of this study is to identify current states and trends of convergence researches by conducting a bibliometric analysis of the papers in the Convergence Society for SMB. After 792 papers from 2012 to 2019 were collected, we analyzed network analysis by using centrality through extracting of nouns and compound nouns with text mining and 3 times of pre-processing and purification processing. According to the results, first, quantitative and qualitative aspects of the researches since 2016 improved, studies focused on words such as influence, convergence, mediating effect, satisfaction, and effect. Second, in the first half (2012-2015), engineering and technical studies were intensively conducted based on topics such as information, system, and security. Third, in the period of the second half (2016-2019), the research scope was expanded to college students, parents, teenagers under the topics of job, self-efficacy, education, satisfaction, depression, and stress. The results of this study are meaningful in identifying existing research trends and in providing information which requires the expansion of new research areas.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.135-142
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• 2020

The purpose of this study is to analyze the effectiveness of university convergence curriculum using CIPP model. With 758 data surveys of professors and students participating in K University's convergence education, the analysis of differences according to group characteristics and the factors affecting performance recognition and course satisfaction were analyzed. As a result of analysis, first, class activity(CA) was the highest (M=3.85), and coursework design(CD) was the lowest (M=3.35), and there were significant differences in the course objectives, course content, and class activities according to the characteristics of the group. Second, the factors affecting the performance recognition and course satisfaction of the convergence curriculum were needs analysis, coursework design, learner activity, performance recognition, and course satisfaction. In conclusion, it suggests that from the planning stage, it should be designed to reflect the needs of professors and students, and to improve satisfaction and performance recognition with novel contents and active teaching and learning activities. This study can be used as basic data for improving the quality of the convergence curriculum.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.135-146
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• 2019

This study was designed to analyze trends in the entire convergence research beyond academic research through social media big data analysis at a time when interdisciplinary convergence research is emphasized along with the fourth industrial revolution. For this purpose, about 150,000 cases of texts and titles were acquired for about 10 years from January 2009 to September 2018 in connection with the convergence research in social media, and word cloud and network analysis were conducted. As a results, the research fields that were actively conducted for each period were eco-tech in 2009 and 2010, smart technology in 2011 and 2012, information and communication in 2013 and 2014, robots in 2015 and 2016, and artificial intelligence in 2017 and 2018. Also, the research areas that have been consistently conducted for about 10 years are culture, design, chemistry, nanotechnology, biotechnology, robot, IT, and information and communication. Since this study identifies trends in convergence research over time, it can be helpful to researchers who are planning convergence research direction by understanding the trends of convergence research.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.411-418
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• 2021

In this study, in order to analyze the AI convergence education courses of 38 graduate schools of education, the analysis frame was constructed in terms of basic subject classification, content field of subject, and detailed subject composition by field. And as a result of analysis through this frame, it was found that the number of subjects currently operated by these graduate schools of education is very different from 14 subjects to 48 subjects. Therefore, it was judged that it was urgent to develop a standard curriculum for the AI convergence education major operated by each graduate school of education for the same purpose. The AI Convergence Education Major, which was established for the same purpose and operated in different forms, will eventually produce teachers with different competencies, so there is a risk of bringing confusion to the direction of AI Convergence Education in the school field.