• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.670-672
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• 2023

본 논문에서는 소셜 미디어 약물 리뷰 데이터로부터 약물 이상 반응을 탐지하는 모델인 FC-BERT 를 기반으로 소셜 네트워크 분석을 활용하여 웹 애플리케이션을 구현하였다. FC-BERT 모델을 거쳐 나온 개체명 인식 결과 중에 같은 의미를 가진 서로 다른 약물 이상 반응 표현들을 MedDRA 부작용 사전을 참고하여 하나의 MedDRA 용어로 표준화하여 매핑했다. 해당 결과에 소셜 네트워크 분석 기법을 적용하여 생성한 상위 15 개의 ADR 동시 출현 그래프를 상위 30 개의 워드 클라우드와 함께 시각화하여 보여주는 웹 애플리케이션을 개발했다. 동시 출현 그래프는 가장 많은 리뷰에서 동시에 나타나는 ADR 쌍을 보여준다. 본 논문에서 제안한 웹 애플리케이션은 사람마다 다르게 나타나는 다양한 약물 이상 반응을 사용자에게 좀 더 접근성이 좋게 제공할 수 있을 것으로 보인다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.2
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• pp.217-239
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• 2015

For bibliotherapy, users should understand their own life situation, select and access the book (self-help book). User access to book through situation catalog (or list) in reading list, but user is difficult to define and simplify in one word after understanding their own situation. Catalog of bibliotherapy reading list classifies books using one situation category or maximum of two categories other than the age-specific classification. In this study, the author approached and analyzes based on the result of the research on the relationship between bibliotherapy and reading list, in order that access more efficiently to book what user wants. Bibliotherapy reading-list by using mapping and crosswalk between categories, and analyzes category of reading lists through comprehensive review.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.513-518
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• 2010

The advancement of information technology along with the proliferation of communication and multimedia has increased the demand of digital contents. Video data of digital contents such as VOD, NOD, Digital Library, IPTV, and UCC are getting more permeated in various application fields. Video data have sequential characteristic besides providing the spatial and temporal information in its 3D format, making searching or browsing ineffective due to long turnaround time. In this paper, we suggest ATVC(Authoring Tool for Video Contents) for solving this issue. ATVC is a video editing tool that detects key frames using visual rhythm and insert metadata such as keywords into key frames via XML tagging. Visual rhythm is applied to map 3D spatial and temporal information to 2D information. Its processing speed is fast because it can get pixel information without IDCT, and it can classify edit-effects such as cut, wipe, and dissolve. Since XML data save key frame information via XML tag and keyword information, it can furnish efficient browsing.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.537-544
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• 2022

As the penetration of electric vehicles and development of new models, user experience factors are getting more important in designing connectivity systems for car infotainment services. The primary object of this study is to identify commonalities and differences by comparing user experience factors in the Korean and US electric vehicle markets. This study derived connectivity keywords by text mining the vehicle introduction on the market in each country, and performed centrality, cluster analysis and visualization mapping using the semantic network analysis. As a result, the Korean new electric vehicle connectivity service mainly focused on driving functions such as driving, parking assistance, and charging, while US focused on device connection, convenience function control, app use, entertainment viewing. Based on the analysis, this study presented the practical implications in marketing, system design, and HMI design.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.1
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• pp.11-18
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• 2018

Two-dimensional (2D) materials such as transition metal dichalcogenides have attracted tremendous scientific interests owing to their potential of solving the zero band-gap issue of graphene. In this work, the research areas and technology evolutionary dynamics of the 2D materials were identified using the scientometric method focusing on keyword mapping and clustering. The time-series analysis showed that the technological progress of 2D material is in the early growth period. The overlay mapping analysis were carried out to investigate the technology evolution of 2D materials with time. The strategic diagram of co-word analysis classifying the topological positions of keyword was derived to support the analysis results. It is conjectured that extensive research will be conducted widely on the application of 2D materials not only in electronic and optoelectronic devices, but also in various other fields such as biomedical applications, and that their development will be more rapid based on accumulated results of extant graphene research.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.77-78
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• 2020

본 논문에서는 미디어 플레이어 제어가 어려운 지체 장애인들을 위해 음성과 동작 인식 기반의 미디어 제어 애플리케이션을 설계하고 구현한다. 이 애플리케이션은 사용자의 음성 인식을 위해 먼저 명령어를 정하고, 명령에 매핑되는 키워드 관리하는 데이터 모델을 생성한다. 그리고 이 데이터 모델을 JSON 파일로 정제하여 사용한다. 그리고 키넥트 센서를 활용한 동작 인식은 오른쪽 어깨를 중심으로 오른쪽 손목의 좌표값을 인식함으로써 동작 인식 제어 컨트롤을 실행한다. 오른쪽 어깨를 기준점으로 오른쪽 손목의 좌표값으로 현재 팔의 위치를 정하고, 영역 1~4 에 따라 동작을 인식한다.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.53-63
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• 2020

Electronic financial transactions are also actively increasing due to the rapid spread of information communication media such as the Internet, smart devices, and IoT, but as a derivative by-product, threats of financial security such as leakage of various personal information and hacking are also increasing. Therefore, the importance of financial security against this is increasing, but in Korea, financial security technology is relatively insufficient compared to advanced countries in the field of financial security, such as Active-X. Therefore, this study aims to present the major development direction in the domestic financial security field by comparing key technology trends with IPC classification frequency analysis, keyword frequency analysis, and keyword network analysis based on domestic and foreign financial security-related patent data. In conclusion, it seems that recent domestic and foreign trends have focused on the development of related technologies according to the development of smart device-based electronic financial services. Accordingly, it is intended to be used as the basis data for technology development of financial security by mapping the trend of financial security research trend and technology trend analysis through thesis data analysis that reflects the research of the preceding aspect as the technology of commercialization in the future.

• Journal of The Korean Association of Information Education
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• v.24 no.4
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• pp.313-325
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• 2020

There is a growing interest and need for the educational use of artificial intelligence as artificial intelligence technologies such as machine learning and deep learning, the core technologies of the intelligent information society, owing to the recent innovative technological advances. Consequently, the Ministry of Education announced the First Information Education Comprehensive Plan for introducing artificial intelligence competence enhancing education into the education field in preparation for the intelligent information society based on artificial intelligence technologies. Therefore, this study collected 416 overseas papers related to the educational use of artificial intelligence from the Web of Science (WoS) in order to explore the potential for using artificial intelligence educationally. This study analyzed the research status and research topic by country, citation counts, network analysis on keywords of the collected data by using the bibliometrix package of R program. Through this, it was possible to identify the research trend on the educational use of artificial intelligence, currently being conducted in foreign countries. It is believed that it will be possible to obtain implications for the topics and directions to be studied in the information education for strengthening artificial intelligence education based on the results of this study.

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.313-334
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• 2021

This study aimed to analyze AI research trends related to elementary, middle, and high school education. To this end, the related literature was collected from the SCOPUS database and the publication period of the collected literature was from 1974 to March 2021, with 154 journal papers and 571 conference papers. Research trends were analyzed based on the co-occurrences analysis technique of 4,521 words of author keyword and index keyword included in these papers. As a result of the analysis, big data, data mining, data science and deep learning were found as the latest research trends with machine learning and there was a difference between elementary, middle and high school education. It can be seen that elementary school had a lot of robot-related research, middle school had a lot of game and data-related research, and high school had various and in-depth research. In discussion, we mapped the top 50 words common to elementary, middle, and high schools with the 'Artificial Intelligence Basics' curriculum of Korean Government and '5 Big Ideas' of the United States Government so that AI research can be viewed at a glance.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.43-57
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• 2022

In this paper, we propose a method of analyzing research papers published by researchers belonging to university departments in the field of disaster & safety for the scientometric analysis of the research status in the field of disaster safety. In order to conduct analysis research, the dataset constructed in previous studies was newly improved and utilized. In detail, for research papers of authors belonging to the disaster prevention and safety engineering type department of domestic universities, institution identification, cited journal identification of references, department type classification, disaster safety type classification, researcher major information, KSIC(Korean Standard Industrial Classification) mapping information was reflected in the experimental data. The proposed method has a difference from previous studies in the field of disaster & safety and data set based on related keyword searches. As a result of the analysis, the type and regional distribution of organizations belonging to the department of disaster prevention and safety engineering, the composition of co-authored department types, the researchers' majors, the status of disaster safety types and standard industry classification, the status of citations in academic journals, and major keywords were identified in detail. In addition, various co-occurrence networks were created and visualized for each analysis unit to identify key connections. The research results will be used to identify and recommend major organizations and information by disaster type for the establishment of an intelligent crisis warning system. In order to provide comprehensive and constant analysis information in the future, it is necessary to expand the analysis scope and automate the identification and classification process for data set construction.