• Journal of KIISE:Databases
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• v.31 no.6
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• pp.609-623
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• 2004

Various metadata registries have been built in many countries of the world. Although the metadata registry is an international standard, it does not provide a consistent access interface for handling the metadata registries. Therefore, all systems for managing them were developed by using different operations and access interfaces. It requires duplicate efforts on the same operations whenever metadata registry systems are developed. As a result, it causes unnecessary costs and efforts for building metadata registries, and also incurs inconsistency between the metadata registries because the previous developed systems use the different interfaces for the metadata registry elements This paper analyzes and defines operation patterns that are commonly used for the metadata registries. We defined and designed SQL/MDR extended from SQL using the analyzed operation patterns. SQL/MDR provides a standardized access interface for developing metadata registry systems. This paper shows the implementation of SQL/MDR and the result that we actually applied it to the bibliographical databases. By developing the metadata registry systems using SQL/MDR, we can reduce much time and efforts owing to its standard interface. It allows metadata registries to be accessed consistently. Additionally, it makes all metadata registries follow the international standard, ISO/IEC ll179.

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.61-72
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• 2020

Social problems, such as economic instability, aging population, heightened competition, and changes in personal values, might become more serious in the near future. Affective computing has received much attention in the scholarly community as a possible solution to potential social problems. Accordingly, we examined domestic and global knowledge structure, major keywords, current research status, international research collaboration, and network for each major keyword, focusing on keywords related to affective computing. We searched for articles on a specialized academic database (Scopus) using major keywords and carried out bibliometric and network analyses. We found that China and the United States (U.S.) have been active in producing knowledge on affective computing, whereas South Korea lags well behind at around 10%. Major keywords surrounding affective computing include computing, processing, affective analysis, research, user modeling categorizing recognitions, and psychological analysis. In terms of international research collaboration structure, China and the U.S. form the largest cluster, whereas other countries like the United Kingdom, Germany, Switzerland, Spain, and Canada have been strong collaborators as well. Contrastingly, South Korea's research has not been diverse and has not been very successful in producing research outcomes. For the advancement of affective computing research in South Korea, the present study suggests strengthening international collaboration with major countries, including the U.S. and China and diversifying its research partners.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.1-11
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• 2021

The purpose of this study was to analyze the trends and characteristics of 'stress urinary incontinence' research through word frequency analysis, and their relationships were modeled using word embedding. Abstract data of 9,868 papers containing abstracts in PubMed's MEDLINE were extracted using a Python program. Then, through frequency analysis, 10 keywords were selected according to the high frequency. The similarity of words related to keywords was analyzed by Word2Vec machine learning algorithm. The locations and distances of words were visualized using the t-SNE technique, and the groups were classified and analyzed. The number of studies related to stress urinary incontinence has increased rapidly since the 1980s. The keywords used most frequently in the abstract of the paper were 'woman', 'urethra', and 'surgery'. Through Word2Vec modeling, words such as 'female', 'urge', and 'symptom' were among the words that showed the highest relevance to the keywords in the study on stress urinary incontinence. In addition, through the t-SNE technique, keywords and related words could be classified into three groups focusing on symptoms, anatomical characteristics, and surgical interventions of stress urinary incontinence. This study is the first to examine trends in stress urinary incontinence-related studies using the keyword frequency analysis and word embedding of the abstract. The results of this study can be used as a basis for future researchers to select the subject and direction of the research field related to stress urinary incontinence.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.99-132
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• 2022

The purpose of this study is to propose AET (Augmented and Extended Topics), a novel method of synthesizing both LDA and BERTopic results, and to analyze the recently published LIS articles as an experimental approach. To achieve the purpose of this study, 55,442 abstracts from 85 LIS journals within the WoS database, which spans from January 2001 to October 2021, were analyzed. AET first constructs a WORD2VEC-based cosine similarity matrix between LDA and BERTopic results, extracts AT (Augmented Topics) by repeating the matrix reordering and segmentation procedures as long as their semantic relations are still valid, and finally determines ET (Extended Topics) by removing any LDA related residual subtopics from the matrix and ordering the rest of them by F₁ (BERTopic topic size rank, Inverse cosine similarity rank). AET, by comparing with the baseline LDA result, shows that AT has effectively concretized the original LDA topic model and ET has discovered new meaningful topics that LDA didn't. When it comes to the qualitative performance evaluation, AT performs better than LDA while ET shows similar performances except in a few cases.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.1-13
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• 2023

The widespread adoption of smartphones and advancements in internet technology have notably shifted content consumption habits toward video. This research aims to dissect the nature of videos posted on YouTube, the global video-sharing platform, to understand the characteristics of both produced and preferred content. For this study, dance was chosen as a specific subject from a variety of video categories. Data on YouTube videos associated with the term "dance" was compiled over three years, from 2019 to 2021. The investigation revealed a clear distinction between the types of dance videos frequently uploaded to YouTube and those that receive a high number of views. The empirical analysis of this study indicates a viewer preference for vlogs that provide insights into the daily lives of dance students, as well as for purpose-driven videos, such as those highlighting dance exam preparations or school dance events. Notably, the vlogs that attract the most attention are typically created by dance students at the college or secondary school level, rather than by professionals. Although the study was focused on dance, its methodologies can be applied to different subjects. These insights are expected to contribute to the development of a recommendation system that aids content creators in effectively targeting their productions.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.21-34
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• 2023

The purpose of this study is to examine the extent of Sustainable Development Goals (SDGs)-related research in the field of entrepreneurship globally since the adoption of the SDGs at the UN General Assembly, and to compare international and domestic research trends in order to determine the direction of SDGs-related research in entrepreneurship in Korea. Utilizing three databases-Web of Science (WoS), KCI, and DBpia- SDGs-related studies in entrepreneurship were extracted by employing specific search terms. After data purification, a total of 356 studies abroad and 4 studies in Korea were used for analysis. After data purification, a total of 356 international studies and 4 Korean studies were analyzed. Due to the limited number of domestic studies, the research trends were examined by conducting frequency analysis and keyword network analysis on international studies alone. Frequency analysis revealed that SDGs research in entrepreneurship primarily focused on sustainability-related terms and was conducted in conjunction with business models, innovation, entrepreneurship education, and strategies. Furthermore, yearly frequency analysis demonstrated an expansion of topics to encompass research on entrepreneurship and SDGs policies, the roles and capabilities of female entrepreneurs in SDGs implementation, energy start-ups and SDGs, directions for implementing SDGs in business schools and SDGs education, indicators for SDGs implementation and evaluation, and technologies for sustainability. The keyword network analysis identified central topics such as business, sustainability, SDGs, innovation, entrepreneurship, business models, and education, with research areas extending to entrepreneurship ecosystems, change and strategy, ethics, and climate. This study holds significance in establishing a foundation for SDGs research in entrepreneurship, which is currently an underexplored area in Korea, by presenting emerging research trends related to SDGs in entrepreneurship.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.207-216
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• 2024

As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.133-162
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• 2024

The rapid digitalization has highlighted the importance of identifying and managing online resources. Especially, the need for a systematic identification system for the efficient distribution and preservation of digital content is growing. This study aims to respond to these contemporary demands by investigating the current state of identification systems for online resources and exploring more systematic management and utilization methods through linking these systems with legal deposit. To achieve this, the study surveyed the identification systems and their issuance status for online resources and analyzed prior research related to these online resources. Based on the analysis, the proposed strategies for linking with legal deposit can be summarized into three categories: First, to prioritize and enhance the utilization of legal deposit, strategies are required to strengthen the mutual complementarity of deposit and use, to assign priorities to certain deposits, and to increase the usability of deposited materials. Second, as strategies based on international standard numbers for linking with legal deposit, it is necessary to integrate ISBN and UCI in the deposit process, to link international standard resource numbers with deposit, to interconnect metadata between international standard numbers and UCI, to integrate UCI and ICN, and to introduce automation technology for upgrading the deposit system. Third, to effectively implement the aforementioned strategies, policy support is essential. This includes enhancing the role of the Korean Bibliographic Standards Center, strengthening cooperation with publishers, compensating for deposited materials, and increasing awareness and institutional compensation for the legal deposit system.

• Journal of the Korea Society for Simulation
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• v.33 no.3
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• pp.13-26
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• 2024

The CBRN(Chemical, Biological, Radiological, and Nuclear) hazard prediction model is a system that supports commanders in making better decisions by creating contamination distribution and damage prediction areas based on the weapons used, terrain, and weather information in the events of biochemical and radiological accidents. NBC_RAMS(Nuclear, Biological and Chemical Reporting And Modeling S/W System) developed by ADD (Agency for Defense Development) is used not only supporting for decision making plan for various military operations and exercises but also for post analyzing CBRN related events. With the NBC_RAMS's core engine, we introduced a CBR hazard assessment scenario analysis system that can generate contaminant distribution prediction results reflecting various CBR scenarios, and described how to apply it in specific purposes in terms of input information, meteorological data, land data with land coverage and DEM, and building data with pologon form. As a practical use case, a technology development case is addressed that tracks the origin location of contaminant source with artificial intelligence and a technology that selects the optimal location of a CBR detection sensor with score data by analyzing large amounts of data generated using the CBRN scenario analysis system. Through this system, it is possible to generate AI-specialized CBRN related to training and analysis data and support planning of operation and exercise by predicting battle field.

• Journal of the Korean Society for information Management
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• v.30 no.1
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• pp.7-32
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• 2013

The goal of the present study is to identify the topic trend in the field of library and information science in Korea. To this end, we collected titles and s of the papers published in four major journals such as Journal of the Korean Society for information Management, Journal of the Korean Society for Library and Information Science, Journal of Korean Library and Information Science Society, and Journal of the Korean BIBLIA Society for library and Information Science during 1970 and 2012. After that, we applied the well-received topic modeling technique, Latent Dirichlet Allocation(LDA), to the collected data sets. The research findings of the study are as follows: 1) Comparison of the extracted topics by LDA with the subject headings of library and information science shows that there are several distinct sub-research domains strongly tied with the field. Those include library and society in the domain of "introduction to library and information science," professionalism, library and information policy in the domain of "library system," library evaluation in the domain of "library management," collection development and management, information service in the domain of "library service," services by library type, user training/information literacy, service evaluation, classification/cataloging/meta-data in the domain of "document organization," bibliometrics/digital libraries/user study/internet/expert system/information retrieval/information system in the domain of "information science," antique documents in the domain of "bibliography," books/publications in the domain of "publication," and archival study. The results indicate that among these sub-domains, information science and library services are two most focused domains. Second, we observe that there is the growing trend in the research topics such as service and evaluation by library type, internet, and meta-data, but the research topics such as book, classification, and cataloging reveal the declining trend. Third, analysis by journal show that in Journal of the Korean Society for information Management, information science related topics appear more frequently than library science related topics whereas library science related topics are more popular in the other three journals studied in this paper.