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Analysis of Domestic Research Trends on Technoparks(1997~2022) (테크노파크 국내 학술 연구동향 분석(1997~2022))

  • Seulbee Lee;Jian Woo;Myungjun Oh
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.47 no.3
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    • pp.104-113
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    • 2024
  • This study aims to examine domestic research trends on technoparks and to explore future research directions in this field. For this purpose, 493 articles were collected from academic journal sites, covering the period from 1997, when the pilot technoparks were designated, to 2022. To avoid duplication of identical titles and content, theses and conference papers were excluded. Only articles registered or candidate-registered in the Korea Citation Index (KCI) were selected. After reviewing the research topics and content, a total of 74 papers were used for the final analysis. The data analysis involved descriptive analyses of the research period, research areas, research methods, research subjects, and research topics. Furthermore, a word cloud text analysis was conducted using 305 keywords related to technoparks. This study is significant as the first comprehensive analysis of research trends on technoparks and aims to provide meaningful foundational data to explore future directions for research and innovation policy related to technoparks.

A study on the classification of research topics based on COVID-19 academic research using Topic modeling (토픽모델링을 활용한 COVID-19 학술 연구 기반 연구 주제 분류에 관한 연구)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.155-174
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    • 2022
  • From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (

    ) were the topic modeling results for each research topic (
    ) was found to be derived from For example, as a result of topic modeling for papers related to 'vaccine', a new topic titled Topic 05 'neutralizing antibodies' was extracted. A neutralizing antibody is an antibody that protects cells from infection when a virus enters the body, and is said to play an important role in the production of therapeutic agents and vaccine development. In addition, as a result of extracting topics from papers related to 'treatment', a new topic called Topic 05 'cytokine' was discovered. A cytokine storm is when the immune cells of our body do not defend against attacks, but attack normal cells. Hidden topics that could not be found for the entire thesis were classified according to keywords, and topic modeling was performed to find detailed topics. In this study, we proposed a method of extracting topics from a large amount of literature using the LDA algorithm and extracting similar words using the Skip-gram method that predicts the similar words as the central word among the Word2vec models. The combination of the LDA model and the Word2vec model tried to show better performance by identifying the relationship between the document and the LDA subject and the relationship between the Word2vec document. In addition, as a clustering method through PCA dimension reduction, a method for intuitively classifying documents by using the t-SNE technique to classify documents with similar themes and forming groups into a structured organization of documents was presented. In a situation where the efforts of many researchers to overcome COVID-19 cannot keep up with the rapid publication of academic papers related to COVID-19, it will reduce the precious time and effort of healthcare professionals and policy makers, and rapidly gain new insights. We hope to help you get It is also expected to be used as basic data for researchers to explore new research directions.

  • A study on the improving and constructing the content for the Sijo database in the Period of Modern Enlightenment (계몽기·근대시조 DB의 개선 및 콘텐츠화 방안 연구)

    • Chang, Chung-Soo
      • Sijohaknonchong
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      • v.44
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      • pp.105-138
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      • 2016
    • Recently with the research function, "XML Digital collection of Sijo Texts in the Period of Modern Enlightenment" DB data is being provided through the Korean Research Memory (http://www.krm.or.kr) and the foundation for the constructing the contents of Sijo Texts in the Period of Modern Enlightenment has been laid. In this paper, by reviewing the characteristics and problems of Digital collection of Sijo Texts in the Period of Modern Enlightenment and searching for the improvement, I tried to find a way to make it into the content. This database has the primary meaning in the integrating and glancing at the vast amounts of Sijo in the Period of Modern Enlightenment to reaching 12,500 pieces. In addition, it is the first Sijo data base which is provide the variety of search features according to literature, name of poet, title of work, original text, per period, and etc. However, this database has the limits to verifying the overall aspects of the Sijo in the Period of Modern Enlightenment. The title and original text, which is written in the archaic word or Chinese character, could not be searched, because the standard type text of modern language is not formatted. And also the works and the individual Sijo works released after 1945 were missing in the database. It is inconvenient to extract the datum according to the poet, because poets are marked in the various ways such as one's real name, nom de plume and etc. To solve this kind of problems and improve the utilization of the database, I proposed the providing the standard type text of modern language, giving the index terms about content, providing the information on the work format and etc. Furthermore, if the Sijo database in the Period of Modern Enlightenment which is prepared the character of the Sijo Culture Information System could be built, it could be connected with the academic, educational contents. For the specific plan, I suggested as follow, - learning support materials for the Modern history and the national territory recognition on the Modern Age - source materials for studying indigenous animals and plants characters creating the commercial characters - applicability as the Sijo learning tool such as Sijo Game.

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    Text Mining-Based Emerging Trend Analysis for the Aviation Industry (항공산업 미래유망분야 선정을 위한 텍스트 마이닝 기반의 트렌드 분석)

    • Kim, Hyun-Jung;Jo, Nam-Ok;Shin, Kyung-Shik
      • Journal of Intelligence and Information Systems
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      • v.21 no.1
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      • pp.65-82
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      • 2015
    • Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

    Literary Text and the Cultural Interpretation - A Study of the Model of 「History of Spanish Literature」 (문학텍스트와 문학적 해석 -「스페인 문학사」를 통한 모델 연구)

    • Na, Songjoo
      • Cross-Cultural Studies
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      • v.26
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      • pp.465-485
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      • 2012
    • Instructing "History of Spanish Literature" class faces various types of limits and obstacles, just as other foreign language literature history classes do. Majority of students enter the university without having any previous spanish learning experience, which means, for them, even the interpretation of the text itself can be difficult. Moreover, the fact that "History of Spanish Literature" is traced all the way back to the Middle Age, students encounter even more difficulties and find factors that make them feel the class is not interesting. To list several, such factors include the embarrassment felt by the students, antiquated expressions, literature texts filled with deliberately broken grammars, explanations written in pretentious vocabularies, disorderly introduction of many different literary works that ignores the big picture, in which in return, reduces academic interest in students, and finally general lack of interest in literate itself due to the fact that the following generation is used to visual media. Although recognizing such problem that causes the distortion of the value of our lives and literature is a very imminent problem, there has not even been a primary discussion on such matter. Thus, the problem of what to teach in "History of Spanish Literature" class remains unsolved so far. Such problem includes wether to teach the history of authors and literature works, or the chronology of the text, the correlations, and what style of writing to teach first among many, and how to teach to read with criticism, and how to effectively utilize the limited class time to teach. However, unfortunately, there has not been any sorts of discussion among the insructors. I, as well, am not so proud of myself either when I question myself of how little and insufficiently did I contemplate about such problems. Living in the era so called the visual media era or the crisis of humanity studies, now there is a strong need to bring some change in the education of literature history. To suggest a solution to make such necessary change, I recommended to incorporate the visual media, the culture or custom that students are accustomed to, to the class. This solution is not only an attempt to introduce various fields to students, superseding the mere literature reserch area, but also the result that reflects the voice of students who come from a different cultural background and generation. Thus, what not to forget is that the bottom line of adopting a new teaching method is to increase the class participation of students and broaden the horizon of the Spanish literature. However, the ultimate goal of "History of Spanish Literature" class is the contemplation about humanity, not the progress in linguistic ability. Similarly, the ultimate goal of university education is to train students to become a successful member of the society. To achieve such goal, cultural approach to the literature text helps not only Spanish learning but also pragmatic education. Moreover, it helps to go beyond of what a mere functional person does. However, despite such optimistic expectations, foreign literature class has to face limits of eclecticism. As for the solution, as mentioned above, the method of teaching that mainly incorporates cultural text is a approach that fulfills the students with sensibility who live in the visual era. Second, it is a three-dimensional and sensible approach for the visual era, not an annotation that searches for any ambiguous vocabularies or metaphors. Third, it is the method that reduces the burdensome amount of reading. Fourth, it triggers interest in students including philosophical, sociocultural, and political ones. Such experience is expected to stimulate the intellectual curiosity in students and moreover motivates them to continues their study in graduate school, because it itself can be an interesting area of study.

    Big Data Analysis of Busan Civil Affairs Using the LDA Topic Modeling Technique (LDA 토픽모델링 기법을 활용한 부산시 민원 빅데이터 분석)

    • Park, Ju-Seop;Lee, Sae-Mi
      • Informatization Policy
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      • v.27 no.2
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      • pp.66-83
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      • 2020
    • Local issues that occur in cities typically garner great attention from the public. While local governments strive to resolve these issues, it is often difficult to effectively eliminate them all, which leads to complaints. In tackling these issues, it is imperative for local governments to use big data to identify the nature of complaints, and proactively provide solutions. This study applies the LDA topic modeling technique to research and analyze trends and patterns in complaints filed online. To this end, 9,625 cases of online complaints submitted to the city of Busan from 2015 to 2017 were analyzed, and 20 topics were identified. From these topics, key topics were singled out, and through analysis of quarterly weighting trends, four "hot" topics(Bus stops, Taxi drivers, Praises, and Administrative handling) and four "cold" topics(CCTV installation, Bus routes, Park facilities including parking, and Festivities issues) were highlighted. The study conducted big data analysis for the identification of trends and patterns in civil affairs and makes an academic impact by encouraging follow-up research. Moreover, the text mining technique used for complaint analysis can be used for other projects requiring big data processing.

    A Service Framework for Supporting XML-based National Research and Development Report Contents (XML 기반 국가연구개발보고서 콘텐츠 서비스의 프레임워크 설계)

    • Shon, Ho-Sun;Lee, Jong-Yun
      • Journal of the Korea Academia-Industrial cooperation Society
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      • v.12 no.1
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      • pp.427-435
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      • 2011
    • The information management system for the national R&D reports on the level of each government department have been operated in order to have special affiliated organizations collect detailed information, construct databases for R&D reports, and operate their information system; thus, the current classification system for the R&D reports on the governmental level is insufficient. Also, each department requires to prepare a standardized electronic original text service system since mutually different electronic original text services have been provided. therefore, this paper sets up the following research goals and detailed research contents. The goals of this study are to establish methods to standardize the forms of national R&D reports and suggest the framework for XML-based national R&D reports services by analyzing the problems in the forms of previous national R&D reports services. As detailed research contents, first, Identify the current R&D electronic original reports services by each government department. Second, this paper analyzed primary overseas science technology information service systems related with national research and development reports and related database schemata. this paper proposed the XML-based national R&D reports service framework through analyzing the problems in the framework of the existing national R&D reports service system and also established and suggested the methods to provide database schema design and report portal services. Lastly, it is expected that this paper will have academic contribution to enhancing R&D investment efficiency by utilizing collaboratively the information and resources related with national R&D through establishing the general information management system for national-dimension R&D reports and also managing science technology information efficiently and developing a user-centered integrated information system.

    Research Suggestion for Disaster Prediction using Safety Report of Korea Government (안전신문고를 이용한 재난 예측 방법론 제안)

    • Lee, Jun;Shin, Jindong;Cho, Sangmyeong;Lee, Sanghwa
      • Journal of Korean Society of Disaster and Security
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      • v.12 no.4
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      • pp.15-26
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      • 2019
    • Anjunshinmungo (The safety e-report) has been in operation since 2014, and there are about 1 million cumulative reports by June 2019. This study analyzes the contents of more than 1 million safety newspapers reported at the present time of information age to determine how powerful and meaningful the people's voice and interest are. In particular, we are interested in forecasting ability. We wanted to check whether the report of the safety newspaper was related to possible disasters. To this end, the researchers received data reported in the safety newspaper as text and analyzed it by natural language analysis methodology. Based on this, the newspaper articles during the analysis of the safety newspaper were analyzed, and the correlation between the contents of the newspaper and the newspaper was analyzed. As a result, accidents occurred within a few months as the number of reports related to response and confirmation increased, and analyzing the contents of safety reports previously reported on social instability can be used to predict future disasters.

    Translational Study on a Chapter of Taeeum-Disease[太陰病篇] in "The Golden Mirror of Medicine.The Notes of Treatise on Cold-Induced Diseases(醫宗金鑑.傷寒論注)" ("의종금감(醫宗金鑑).정정중경전서상한론주(訂正仲景全書傷寒論註)" "변태음병맥증병치전편(辨太陰病脈證幷治全篇)"에 대한 번역연구)

    • Lee, Yong-Bum
      • Journal of Korean Medical classics
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      • v.23 no.2
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      • pp.33-62
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      • 2010
    • "The Golden Mirror of Medicine(醫宗金鑑)" was compiled by the medical officers of the Cheong(淸) government headed by Ogyeom(吳謙: 1736-1795) in 1742, and was adopted as a textbook by the Institute of Imperial Physicians(太醫院) in 1749. This book provides a good summary of academic contents and clinical experiences from before the Cheong(淸) dynasty, and serves as a convenient and practical guide book. "The Notes of Treatise on Cold-Induced Diseases(傷寒論注)" is one part of "The Golden Mirror of Medicine(醫宗金鑑)", and this is placed at the beginning of the book, indicating its importance. The chapter on taeeum-disease[太陰病篇], which is the third part of "The Notes of the Treatise on Cold-Induced Diseases(傷寒論注)", has not yet been translated into Korean. Therefore, in this study, the characteristics of Ogyeom's(吳謙) notes are inspected through a comparative study of the chapter of taeeum-disease[太陰病篇] based on translation and the notes of famous scholars. The texts first provide an outline of taeeum-disease[太陰病], which is followed by diarrhea, vomiting and therapeutic methods of syndrome involving both the exterior and interior[表裏兼證], as well as abdominal distension and pain. The prognoses are then explained in succession. The eight texts that have been shown in the chapter of taeeum-disease[太陰病篇] of original text were relocated and the seven texts that existed in the chapters of taeyang(太陽), yangmyeong(陽明) and gwol-eum(厥陰) were moved to this chapter. Furthermore, Ogyeom(吳謙) moved the cold-dysphagia[寒格] text from a chapter of gwol-eum-disease[厥陰病] to a chapter of taeeum-disease[太陰病] and explained vomiting due to pathogenic cold. The origins of taeeum-disease[太陰病] are purported to occur through the yang-channel[陽經] to the eum-channel[陰經], and taeeum-disease[太陰病] was reported to include both interior-deficiency-cold-syndrome[裏虛寒證] and interior-excess-heat-syndrome[裏實熱證]. In the case of diarrhea-more-severe-symptoms[自利益甚], he thought it induced by faultpurgation[誤下], and in indication for decoction of cinnamon with peony[桂枝加芍藥湯] and decoction of cinnamon with rhubarb[桂枝加大黃湯], he thought it included the exterior syndrome of taeyang-disease[太陽表證], and rhubarb was used in purgation of taeeum-excess[太陰實].

    A Development Plan for Co-creation-based Smart City through the Trend Analysis of Internet of Things (사물인터넷 동향분석을 통한 Co-creation기반 스마트시티 구축 방안)

    • Park, Ju Seop;Hong, Soon-Goo;Kim, Na Rang
      • Journal of Korea Society of Industrial Information Systems
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      • v.21 no.4
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      • pp.67-78
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      • 2016
    • Recently many countries around the world are actively promoting smart city projects to address various urban problems such as traffic congestion, housing shortage, and energy scarcity. Due to development of the Internet of Things (IoT), the development of a smart city with sustainability, convenience, and environment-friendliness was enabled through the effective control and reuse of urban resources. The purpose of this study is to analyze the technical trends of IoT and present a development plan for smart city which is one of the applications of the IoT. To this end, the news articles of the Electronic Times between 2013 and 2015were analyzed using the text mining technique and smart city development cases of other countries were investigated. The analysis results revealed the close relationships of big data, cloud, platforms, and sensors with smart city. For the successful development of a smart city, first, all the interested parties in the city must work together to create new values throughout the entire process of value chain. Second, they must utilize big data and disclose public data more actively than they are doing now. This study has made academic contribution in that it has presented a big data analysis method and stimulated follow-up studies. For the practical contribution, the results of this study provided useful data for the policy making of local governments and administrative agencies for smart city development. This study may have limitations in the incorporation of the total trends because only the news articles of the Electronic Times were selected to analyze the technical trends of the IoT.


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