• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3210-3219
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• 2015

This study attempts to search for potential users of patents developed by public research institutes, emphasizing the importance of identifying potential users for successful technology marketing. On the basis of the theoretical argument that technological development show path-dependence, we analyzed patent citation network of a technology developed by a Korean public research institute to achieve the purpose of this research. The result shows that the potential users identified from our method are different from the institute's initial expectation. Therefore, we argue that the method using patent citation network is useful and effective for public research institutes' technology marketing. Lastly we suggest a new framework for technology marketing process in public research institutes.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.841-845
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• 2009

The independent cascade model has been widely used to analyze information diffusion in the blog world. In this paper, we propose a new method to construct a blog network for applying the independent cascade model to analyzing of information diffusion in a blog world. To construct a blog network, the proposed method establishes the edge between two users and calculates diffusion probabilities between them by analyzing the activities happened between two users. To calculate diffusion probabilities, the method exploits the ratio of the number of documents actually diffused to a specific user to that of documents written for the purpose of being diffused to other blogs. The experimental result using a real world blog data demonstrates that our method reflects actual information diffusion in a blog world better than existing ones.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.359-367
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• 2021

The purpose of this study is to analyze domestic patient safety culture research topics using text mining and CONCOR analysis. The research method was conducted in the stages of data collection, data preprocessing, text mining and social network analysis, and CONCOR analysis. A total of 136 articles were analyzed excluding papers that were not published. Data analysis was performed using Textom and UCINET programs. As a result of this study, TF (frequency) of patient safety culture-related studies showed that patient safety was the highest, and TF-IDF (importance in documents) was highest in nursing. As a result of the CONCOR analysis, a total of seven clusters were derived: knowledge and attitude, communication, medical service, team, work environment, structure, organization and management that constitute the patient safety culture. In the future, it is necessary to conduct research on the relationship between the establishment of a patient safety culture and patient outcomes.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.47-60
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• 2019

The purpose of this study is to explore the overall structural relationship between the statutory provisions of nuclear energy legislation and to identify the coherence of the nuclear law system using social network analysis. In particular, we analyze the legal structure of the "Nuclear Safety Act", which plays a central role in nuclear safety regulation, to examine the key provisions in legal network structure of Nuclear Safety Act. Therefore, we found the structural problems of the nuclear legal system and suggest the legislative improvement plan for reducing excessive legislative activity and determining the need for legal amendments in nuclear safety management and regulation. This study is expected to provide a analytical framework for making legal system of further policy in other science and technology industries as well as nuclear energy related industries.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.211-217
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• 2019

As the widespread use of mobile health intervention among Korean patients with chronic disease, it is needed to identify research trends in mobile health intervention on chronic care using text mining technique. This secondary data analysis was conducted to investigate characteristics and main research topics in intervention studies from 2005 to 2018 with a total of 20 peer reviewed articles. Microsoft Excel and Text Analyzer were used for data analysis. Mobile health interventions were mainly applied to hypertension, diabetes, stroke, and coronary artery disease. The most common type of intervention was to develop mobile application. Lately, 'feasibility', 'mobile health', and 'outcome measure' were frequently presented. Future larger studies are needed to identify the relationships among key terms and the effectiveness of mobile health intervention using social network analysis.

• Convergence Security Journal
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• v.20 no.4
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• pp.47-59
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• 2020

The Army, which is dreaming of a military leap forward through the fourth industrial revolution, needs to also consider the side effects and adverse functions of the fourth industrial revolution. In particular, this study conducted an analysis of whether it was consistent with the global technological trend of normal 'military security'. This paper focuses on the countermeasures that could result from 4th industrial revolution by utilizing the text-mining technique and social network technique of big data. 1. Active promotion of a convergence program with private, public, militaryand industrial, academic, and solidarity, 2. Information Sharing for International Cooperation and Cooperation in Cyber security, 3. Military Innovation and Military Unsymmetric Cyber security innovation, 4.The Establishment of Military Security Convergence Interface Management System in accordance with the Fourth Industrial Revolution, 5. Cooperation in the transition from technology engineering to social technology, 6. Establishing a military security governance system in the military, 7. Specifying confidential military digital data We look forward to providing useful information so that the results of this study can help develop the military and enhance military confidentiality.

• Journal of Korean society of Dental Hygiene
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• v.23 no.4
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• pp.269-276
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• 2023

Objectives: This study aimed to analyze the official Instagram accounts of dental hygiene departments, focusing on the relationship between the number of posts and the number of followers. Additionally, the study sought to determine the status of these Instagram accounts through classifying posts by type. Methods: A total of 49 official Instagram accounts from Korean dental hygiene departments were selected as subjects. Correlation and regression analyses were conducted using SPSS ver. 26.0 Statistics software to determine the correlation between the total number of posts and the number of followers. Results: The results indicated a statistically significant difference in follower numbers between 3 year colleges (Mean: 284.11) and 4 year universities (Mean: 167.86), based on university classification (p=0.035). Correlation analysis demonstrated that the number of posts had a significant effect on the number of followers (r=0.338, p=0.017). Conclusions: The findings showed that the differences in Instagram follower numbers and the number of posts among different university classifications significantly influenced the number of followers.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.169-178
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• 2009

There are various approaches that retrieve information from video. However, previous approaches have considered just object information and relationship between objects without story information to retrieve contents. To retrieve exact information at video, we need analyzing approach based on characters and community since these are body of story proceeding. Therefore, this paper describes video information retrieval methodology based on character information. Characters progress story to form relationship through conversations. We can analyze the relationship between characters in a story with the methods that classifies role grades and clusters communities of characters. In this paper, for these, we propose the Character-net and describe how to classify role grades and cluster communities at Character-net. And we show this method to be efficient.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.246-262
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• 2023

The purpose of this study is to identify the major peacekeeping activities that the Korean armed forces has performed from the past to the present. To do this, we collected 692 press releases from the National Defense Daily over the past 20 years and performed topic modeling and social network analysis. As a result of topic modeling analysis, 112 major keywords and 8 topics were derived, and as a result of examining the Korean armed forces's peacekeeping activities based on the topics, 6 major activities and 2 related matters were identified. The six major activities were 'Northeast Asian defense cooperation', 'multinational force activities', 'civil operations', 'defense diplomacy', 'ceasefire monitoring group', and 'pro-Korean activities', and 'general troop deployment' related to troop deployment in general. Next, social network analysis was performed to examine the relationship between keywords and major keywords related to topic decision, and the keywords 'overseas', 'dispatch', and 'high level' were derived as key words in the network. This study is meaningful in that it first examined the topic of the Korean armed forces's peacekeeping activities over the past 20 years by applying big data techniques based on the National Defense Daily, an unstructured document. In addition, it is expected that the derived topics can be used as a basis for exploring the direction of development of Korea's peacekeeping activities in the future.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.121-131
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• 2024

This research explores the potential of leveraging unstructured data from construction supervision documents, which contain detailed inspection insights from independent third-party monitors of building construction processes. With the evolution of analytical methodologies, such unstructured data has been recognized as a valuable source of information, offering diverse insights. The study introduces a framework designed to assess cost performance by applying advanced analytical methods to the unstructured data found in final construction supervision reports. Specifically, key phrases were identified using text mining and social network analysis techniques, and these phrases were then analyzed through binomial logistic regression to assess cost performance. The study found that predictions of cost performance based on unstructured data from supervision documents achieved an accuracy rate of approximately 73%. The findings of this research are anticipated to serve as a foundational resource for analyzing various forms of unstructured data generated within the construction sector in future projects.