• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.1-10
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• 2018

Purpose: This paper provides an idea on the future prospect for change in steps of the six sigma DMAIC project under the environment of the 4th industrial revolution. Methods: First, the purpose and activities required in each step of DMAIC are reviewed. Next, activities are reviewed together with tools and techniques, considering the purpose and the environmental changes of the 4th Industrial Revolution. Finally, the best approaches for achieving the purpose are prospected to get an idea on future change. Results: The purpose of each phase of DMAIC is expected to remain unchanged. But activities, techniques, or methods will be replaced with more effective and efficient ones. Also, many activities may possibly be executed by a system instead of people like BB, GB or team members. Moreover, DMAIC may not be a project any more but a routine job of the system in the future. Conclusion: Under the environment of the 4th industrial revolution, many activities including analyzing various types of data and extracting valuable information, will be executed by a system with proper algorithms instead of people. And six sigma improvement projects may be intrinsic parts of the system and may not exist as separate projects any more.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.247-259
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• 2021

This study aimed to look for educational ways to prepare for the future society for education and people of talent who will lead the post-COVID-19 era. To this end, the factors necessary for the type of future talent in the post-COVID-19 era were identified by analyzing Big data. Based on the deducted factors composing the type of talent in the post-COVID-19 era, policy direction according to the emergence of the post-COVID-19 era were deducted through the interviews with the group of experts and delphi survey, and on the basis of this, this study sought for"a plan for the educational change in line with cultivation of people of talent in the post-COVID-19 era. The results of this study are as follows. First, through the big data analytics and analysis of the interviews, convergence, ICT utilization ability, creativity, self-regulated competency and leadership were found to be the factors necessary for the type of talent in the post-COVID-19 era. Second, it considered the innovation of digital education system and the support for vulnerable classes as the issue for cultivation of people of talent in the post-COVID-19 era. Third, the most important policy with regard to the educational direction for cultivation of people of talent in the post-COVID-19 era was cultivation of convergence talents. Convergence is a very important variable in the post-COVID-19 era since it creates new values by connecting things that are separated from each other. Hopefully, this study will build a basis for competency development, education and training in preparation for the post-COVID-19 era.

• Journal of Digital Convergence
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• v.16 no.3
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• pp.201-210
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• 2018

WorldJob+, being operated by The Human Resources Development Service of Korea, provides a recruitment support services to overseas companies wanting to hire talented Korean applicants and interns, and support the entire course from overseas advancement information check to enrollment, interview, and learning for young job-seekers. More than 300,000 young people have registered in WorldJob+, an overseas united information network, for job placement. To innovate WorldJob+'s services for young job-seekers, Splunk, a powerful platform for analyzing machine data, was introduced to collate and view system log files collected from its website. Leveraging Splunk's built-in data visualization and analytical features, WorldJob+ has built custom tools to gain insight into the operation of the recruitment supporting service system and to increase its integrity. Use cases include descriptive and predictive analytics for matching up services to allow employers and job seekers to be matched based on their respective needs and profiles, and connect jobseekers with the best recruiters and employers on the market, helping job seekers secure the best jobs fast. This paper will cover the numerous ways WorldJob+ has leveraged Splunk to improve its recruitment supporting services.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.207-216
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• 2021

Recently, there is increasing interest in attracting local tourist in the city to revitalize the local economy. For this purpose, customized tourism strategies based on the analysis of travel routes and consumption patterns are becoming important. However, existing studies either focused on limited mainstream tourist analysis or lacked analysis of tourists' behavior-based data perspectives. Therefore, this study aims to present a big data-based tourism strategy that provides customized information by analyzing the demand of individual travelers in details based on mobile service data and card expenditure data generated by the travelers in Yongin city. By tracing those data, this study visualized the tourists' itinerary and their expenditure patterns. The analysis of data from July 2017 to June 2018 shows that men tend to consume in various areas compared to women. It also shows consumption areas for people in their 30s and 40s are similar, whereas those in their 20s do not vary. Using the big data based on Geographic Information system, this study provides strategic insights to administrative personnel who are in charge of tour policy.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

• Information Systems Review
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• v.19 no.2
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• pp.115-136
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• 2017

Online communities have become substantial aspects of people's daily lives. However, only a few communities succeed and attract the majority of users, whereas the vast majority struggle for survival. When various communities coexist, important factors should be identified and examined to maintain attraction and achieve success. The concept of coexistence as been extensively explored in organizational ecology literature. However, given the similarities and differences between online communities and traditional organizations, the direct application of organizational theories to online contexts should be cautiously explored. In this study, we follow the roadmap proposed by Davis et al. (2007) in conducting agent-based modeling and simulation study to develop a novel theory based on the previous literature. In the case of two coexisting communities, we find that community size and participation costs can significantly affect the development of a community. A large community can attract a high number of active members who frequently log in. By contrast, low participation costs can encourage the reading and posting behaviors of members. We also observe the important influence of the distribution of interests on the topic trends of communities. A community composed of a population that focuses on only one topic can quickly converge on the topic regardless of whether the initial topic is broad or focused. This simulation model provides theoretical implications to literature and practical guidance to operators of online communities.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.5-18
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• 2014

This exploratory study investigates the use of a computational knowledge engine (WolframAlpha) and social networking sites (Gmail, Yahoo and Facebook) by 200 students at De La Salle-College of Saint Benilde, their "friends" and their "friends of friends" during the 2009 through 2013 school years, and how this appears to have added value in knowledge generation. The primary aim is to identify what enhances productiveness in knowledge generation in Philippine Tertiary Education. The phenomenological approach is used, therefore there are no specific research questions or hypotheses proposed in this paper. Considering that knowledge generation is a complex phenomenon, a stochastic modelling approach is also used for the investigation that was developed specifically to study un-deterministic complex systems. A list of salient features for knowledge generation is presented as a result. In addition to these features, various problem types are identified from literature. These are then integrated to provide a proposed framework of inclusive (friendly) and innovative social networks, for knowledge generation in Philippine tertiary education. Such a framework is necessarily multidisciplinary and useful for problem-solving in a globalized and pluralist reality. The implementation of this framework is illustrated in the three parts of the study: Part 1: Online lessons, discussions, and examinations in General Psychology, Introduction to Sociology, and Life and Works of Jose Rizal, for the author's students in De La Salle-College of Saint Benilde; Part 2: Facebook Report analytics of students and teachers, their friends and their friends of friends via WolframAlpha; and Part 3: Social Network Analysis of the people and groups influencing the courses' scope-and-sequence in the new General Education Curriculum for Tertiary Schools and Institutions in the Philippines.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.214-220
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• 2021

With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.

• Clinics in Shoulder and Elbow
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• v.26 no.1
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• pp.55-63
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• 2023

Background: Common questions about shoulder arthroplasty (SA) searched online by patients and the quality of this content are unknown. The purpose of this study is to uncover questions SA patients search online and determine types and quality of webpages encountered. Methods: The "People also ask" section of Google Search was queried to return 900 questions and associated webpages for general, anatomic, and reverse SA. Questions and webpages were categorized using the Rothwell classification of questions and assessed for quality using the Journal of the American Medical Association (JAMA) benchmark criteria. Results: According to Rothwell classification, the composition of questions was fact (54.0%), value (24.7%), and policy (21.3%). The most common webpage categories were medical practice (24.6%), academic (23.2%), and medical information sites (14.4%). Journal articles represented 8.9% of results. The average JAMA score for all webpages was 1.69. Journals had the highest average JAMA score (3.91), while medical practice sites had the lowest (0.89). The most common question was, "How long does it take to recover from shoulder replacement?" Conclusions: The most common questions SA patients ask online involve specific postoperative activities and the timeline of recovery. Most information is from low-quality, non-peer-reviewed websites, highlighting the need for improvement in online resources. By understanding the questions patients are asking online, surgeons can tailor preoperative education to common patient concerns and improve postoperative outcomes. Level of evidence: IV.

• Smart Media Journal
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• v.12 no.6
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• pp.15-26
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• 2023

As face-to-face communication has become difficult due to the COVID-19 pandemic, studies have been conducted to understand the impact of non-face-to-face communication, but there is a lack of research that examines this through messenger application reviews. This study aims to identify the impact of the pandemic through Latent Dirichlet Allocation (LDA) topic modeling by collecting review data of 메신저 applications in the Google Play Store and suggest service strategies accordingly. The study categorized the data based on when the pandemic started and the ratings given by users. The analysis showed that messenger is mainly used by middle-aged and older people, and that family communication increased after the pandemic. Users expressed frustration with the application's updates and found it difficult to adapt to the changes. This calls for a development approach that adjusts the frequency of updates and actively listens to user feedback. Also, providing an intuitive and simple user interface (UI) is expected to improve user satisfaction.