• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.217-225
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• 2019

National research and development(R&D) information is information generated in the process of performing R&D based on programs and projects issued by national government departments, and includes information from various research fields as ordered by various departments. Therefore, for efficient R&D information retrieval, it is necessary to build a national R&D terminology dictionary that can reflect the characteristics of such national R&D information. In this study, we propose a method for constructing a national R&D terminology dictionary by applying the classification of science and technology standards used to specify the research field in national R&D information. We will discuss the structural characteristics of national R&D project information and the usefulness of the project keyword, and explain the status of national R&D information by the National Standard Science and Technology Classification(NSSTC) Codes and the characteristics of the national R&D terminologies. Based on this, a method for building a national R&D terminology dictionary is defined in terms of the type and structure of the terminology dictionary, preliminary construction procedures, and refining rules. The national R&D terminology dictionary built on the basis of this study can be used in various ways such as expansion of search terms using Korean-English equivalent words and synonyms when searching national R&D information, clarifying the scope of search using NSSTC, and providing user convenience functions using term explanation information.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.2
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• pp.164-172
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• 2021

Purpose: The purpose of this study was to analyze the level of interest that common Internet users have in dental implant using a Google Trends, and to compare the level of interest with big data from National Health Insurance Service. Materials and methods: Google Trends provides a relative search volume for search keywords, which is the average data that visualizes the frequency of searches for those keywords over a specific period of time. Implant was selected as the search keyword to evaluate changes in time flows of general Internet users' interest from 2015 to 2019 with trend line and 6 month moving average. Relative search volume for implant was analyzed with the number of patients who received National Health Insurance coverage for implant. Interest in implant and conventional denture was compared and popular related search keywords were analyzed. Results: Relative search volume for implant has increased gradually and showed a significant positive correlation with the total number of patients (P<.01). Interest in implant was higher than denture for most of the time. Keywords related to implant cost were most frequently observed in all years and related search on implant procedure was increasing. Conclusion: Within the limitations of this study, the public interest in dental implant was gradually increasing and specific areas of interest were changing. Web-based Google Trends data was also compared with traditional data and significant correlation was confirmed.

• Informatization Policy
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• v.25 no.4
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• pp.37-64
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• 2018

This study aims to forecast the future of the Korean society via a big data analysis. Based upon two sets of database - a collection of 46,000,000 news on 127 media in Naver Portal operated by Naver Corporation and a collection of 70,000 academic papers of social sciences registered in KCI (Korea Citation Index of National Research Foundation) between 2005-2017, 40 most frequently occurring keywords were selected. Next, their temporal variations were traced and compared in terms of number and pattern of frequencies. In addition, core issues of the future were identified through keyword network analysis. In the case of the media news database, such issues as economy, polity or technology turned out to be the top ranked ones. As to the academic paper database, however, top ranking issues are those of feeling, working or living. Referring to the system and life-world conceptual framework suggested by $J{\ddot{u}}rgen$ Habermas, public interest of the future inclines to the matter of 'system' while professional interest of the future leans to that of 'life-world.' Given the disparity of future interest, a 'mismatch paradigm' is proposed as an alternative to social forecasting, which can substitute the existing paradigms based on the ideas of deficiency or deprivation.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.1-8
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• 2021

In the political field of news articles, there are polarized and biased characteristics such as conservative and liberal, which is called political bias. We constructed keyword-based dataset to classify bias of news articles. Most embedding researches represent a sentence with sequence of morphemes. In our work, we expect that the number of unknown tokens will be reduced if the sentences are constituted by subwords that are segmented by the language model. We propose a document embedding model with subword tokenization and apply this model to SVM and feedforward neural network structure to classify the political bias. As a result of comparing the performance of the document embedding model with morphological analysis, the document embedding model with subwords showed the highest accuracy at 78.22%. It was confirmed that the number of unknown tokens was reduced by subword tokenization. Using the best performance embedding model in our bias classification task, we extract the keywords based on politicians. The bias of keywords was verified by the average similarity with the vector of politicians from each political tendency.

• The Journal of Bigdata
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• v.5 no.2
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• pp.121-133
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• 2020

This study was carried out to set the direction of the new industry policy of Busan city by analyzing the changing trend of artificial intelligence technology that has recently developed rapidly and predicting the direction of future development. The company wanted to draw up support measures to utilize artificial intelligence technology, which has been rapidly emerging in the market, in the region's specialized industry. Artificial intelligence is a key keyword in the fourth industrial revolution and artificial intelligence-based data utilization technology can be used in various fields from manufacturing processes to services, and is entering an era of super-fusion in which barriers between technologies and industries will be broken down. In this study, the direction of promotion for fostering Busan as an artificial intelligence city was derived based on the comparison and analysis of artificial intelligence-related ecosystems among major local governments. In this study, we wanted to present a plan to create an artificial intelligence industrial ecosystem that can be called a key policy to foster Busan as an 'AI City'. Busan's plan to foster the AI industry ecosystem is aimed at establishing a policy direction to ultimately nurture the artificial intelligence industry as Busan's future food source.

• Convergence Security Journal
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• v.20 no.4
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• pp.27-34
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• 2020

Recently, the fourth industrial revolution technology has not only changed everyday life greatly through technological development, but has also become a major keyword in the establishment of defense policy. In particular, Internet of Things, cloud, big data, mobile and cybersecurity technologies, called ICBMS, were selected as core leading technologies in defense information policy along with artificial intelligence. Amid the growing importance of the fourth industrial revolution technology, research is being carried out to develop the C4I system, which is currently operated separately by the Joint Chiefs of Staff and each military, including the KJCCS, ATCIS, KNCCS and AFCCS, into an integrated system in preparation for future warfare. This is to solve the problem of reduced interoperability for joint operations, such as information exchange, by operating the C4I system for each domain. In addition, systems such as the establishment of an integrated C4I system and the U.S. military's Risk Management Framework (RMF) are essential for efficient control and safe operation of weapons systems as they are being developed into super-connected and super-intelligent systems. Therefore, in this paper, the intelligent cyber threat detection, management of users' access to information, and intelligent management and visualization of cyber threat are presented in the future C4I system based on big data/cloud.

• Korean Association of Arts Management
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• no.53
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• pp.207-247
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• 2020

is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.36 no.2
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• pp.60-75
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• 2023

Objectives : A bibliometric approach using network analysis was applied to explore the global trends of research on herbal medicine for atopic treatment. Methods : Articles related to herbal medicine on atopic treatment from 2003 to 2022 were retrieved from Web of Science Core Collection. Extracted records were analyzed according to the publication year, research area, journal title, country, organization, author and keyword. The VOSviewer program was used to visualize the trends and the research hotspots in herbal medicine for atopy. Results : Analysis of 406 articles indicated the consistent increase of using herbal medicine for atopic treatment over the last 20 years. The most productive country and research organization in issuing articles were South Korea and Kyunghee university. Many articles have been published in research areas such as 'integrative complementary medicine' and 'pharmacology pharmacy'. By evaluating the total link strength, the average publication year and the average citations of countries and authors, the influential countries and authors were identified. A network analysis based on the co-occurrence and the publication year of keywords revealed the relevant characteristics and trends of herbal medicine for atopy. The most up-to-date keywords were 'topical application', 'skin barrier' and 'care'. Conclusions : This bibliometric study examined the overall trends and the time-based development of herbal medicine for atopic treatment. The current study would be useful not only for grasping the global network hub of research on herbal medicine for atopic treatment, but also to explore the new directions for future research.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.227-253
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• 2023

The study is a preliminary study to conceptualize memes as information resources for literacy education in information environment changed with digital revolution. The study is to explain the context and reality of memes in order to promote the utilization of memes as information resources. The research questions are as follows: First, what topics are 'memes' studied with? Second, what things are captured and studied as 'memes'? The study conducted frequency and co-occurrence network analysis on 145 domestic studies and contents analysis on 73 domestic studies. The results are as follows: First, memes were mainly studied in the fields of 'humanities', 'social sciences', 'interdiciplinary studies', and 'arts and kinesiology'. Studies based on Dawkins' concept of memes (around 2012), studies on introducing the concept of memes to explain the spread of Korean Wave content (around 2015), and independent studies of memes as a major research topic in cultural sociology (around 2019) were performed. Second, memes are linguistic. Language memes (L-memes) are 102 (37%), language-visual memes (LV-memes) are 23 (8%), language-visual-musical memes (LVM-memes) are 21 (8%). Keyword 'language meme' ranked high in frequency, degree centrality and betweenness centrality of co-occurrence network. In other words, memes are expanding as a unique information phenomenon of cultural sociology based on linguistic characteristics. It is necessary to conceptualize meme literacy in terms of information literacy.

• Journal of the Korean Society for information Management
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• v.40 no.1
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• pp.121-148
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• 2023

The purpose of this study is to propose a scholarly paper recommendation system based on metadata attribute similarity with excellent performance. This study suggests a scholarly paper recommendation method that combines techniques from two sub-fields of Library and Information Science, namely metadata use in Information Organization and co-citation analysis, author bibliographic coupling, co-occurrence frequency, and cosine similarity in Bibliometrics. To conduct experiments, a total of 9,643 paper metadata related to "inequality" and "divide" were collected and refined to derive relative coordinate values between author, keyword, and title attributes using cosine similarity. The study then conducted experiments to select weight conditions and dimension numbers that resulted in a good performance. The results were presented and evaluated by users, and based on this, the study conducted discussions centered on the research questions through reference node and recommendation combination characteristic analysis, conjoint analysis, and results from comparative analysis. Overall, the study showed that the performance was excellent when author-related attributes were used alone or in combination with title-related attributes. If the technique proposed in this study is utilized and a wide range of samples are secured, it could help improve the performance of recommendation techniques not only in the field of literature recommendation in information services but also in various other fields in society.