• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.63-73
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• 2018

Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.19-30
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• 2023

An electric scooter(e-scooter), one popularized micro-mobility vehicle has shown rapidly increasing use in many cities. In South Korea, the use of e-scooters has greatly increased, as some companies have launched e-scooter sharing services in a few large cities, starting with Seoul in 2018. However, the use of e-scooters is still controversial because of issues such as parking and safety. Since the perception toward the means of transportation affects the mode choice, it is necessary to track the trends for electric scooters to make the use of e-scooters more active. Hence, this study aimed to analyze the trends related to e-scooters. For this purpose, we analyzed news articles related to e-scooters published from 2014 to 2020 using dynamic topic modeling to extract issues and sentiment analysis to investigate how the degree of positive and negative opinions in news articles had changed. As a result of topic modeling, it was possible to extract three different topics related to micro-mobility technologies, shared e-scooter services, and regulations for micro-mobility, and the proportion of the topic for regulations for micro-mobility increased as shared e-scooter services increased in recent years. In addition, the top positive words included quick, enjoyable, and easy, whereas the top negative words included threat, complaint, and ilegal, which implies that people satisfied with the convenience of e-scooter or e-scooter sharing services, but safety and parking issues should be addressed for micro-mobility services to become more active. In conclusion, this study was able to understand how issues and social trends related to e-scooters have changed, and to determine the issues that need to be addressed. Moreover, it is expected that the research framework using dynamic topic modeling and sentiment analysis will be helpful in determining social trends on various areas.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.75-87
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• 2020

The present study determined new value that can be created through the convergence between artificial intelligence technology (AIT) and all industries by deriving and thoroughly analyzing major issues related to artificial intelligence (AI). This study analyzes domestic articles related to AI using topic modeling method based on LDA algorithm. Keywords were extracted from 3,889 articles of eleven metropolitan newspapers, eight business newspapers and major broadcasting companies; articles were selected by searching for the keyword "artificial intelligence". Keywords were extracted by optimizing the relevance parameter λ to improve the measure of pointwise mutual information (PMI), which shows the association among the keywords of each topic, and topic names were inferred from keywords based on valid evidence. The extracted topics widely showed changes occurring throughout society, economy, industries, culture, and the support policy and vision of the government.

• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.245-253
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• 2019

Beach lifeguards in Korea are unprepared to perform the rescue and safety management for individuals with disabilities. There is no lifeguard training that offers information regarding the rescue of individuals with disabilities. The purpose of the study was to conduct literature review and determine significant issues related to beach lifeguard and provide suggestions for lifeguard training programs and water safety for individuals with disabilities. Databases (i.e., CINAHL Plus with Full Text, ERIC, MEDLINE, SPORTDiscus with Full Text) were used to search research articles and organizational documents. To find relevant documents, search terms such as water safety, lifeguard, drown prevention were used. Data were content analyzed to identify key issues. Based on the literature review, five critical issues regarding rescue of individuals with disabilities, drown prevention, and water safety were drawn and discussed in the article.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.536-548
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• 2018

Public data has been transformed from provider-oriented information disclosure to a form of personalized information sharing centered on individual citizens since government 3.0. As a result, the government is implementing policies and projects to maximize the value of public data and increase reuse. This study analyzes the issues related to public data in the news and seeks the status of government agencies and government projects by issue. We conducted semantic analysis on domestic online news and public agency bidding information including public data and conducted the work of linking major key words derived with social and economic values inherent in public data. As a result, major issues related to public data were divided into broader access to public data, growth of new technology, cooperation and conflict among stakeholders, and utilization of the private sector, which were closely related to transparency, efficiency, participation, and innovation mechanisms. Also major agencies of four issues include the Ministry of Strategy and Finance and Seoul, Ministry of Culture, Sports and Tourism and Gyeonggi-do, Ministry of Trade, Industry and Energy and Incheon, and Ministry of Land, Infrastructure and Transport and Gyeongsangbuk-do. Most of the issues are being led by the government.

• Journal of Digital Convergence
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• v.18 no.9
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• pp.181-190
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• 2020

The purpose of this study is to analyze the trends of wearable keywords using text mining methodology. To this end, 11,952 newspaper articles were collected from 1992 to 2019, and frequency analysis and bi-gram analysis were applied. The frequency analysis showed that Samsung Electronics, LG Electronics, and Apple were extracted as the highest frequency words, and smart watches and smart bands continued to emerge as higher frequency in terms of devices. As a result of the analysis of the bi-gram, it was confirmed that the sequence of two adjacent words such as world-first and world-largest appeared continuously, and related new bi-gram words were derived whenever issues or events occurred. This trend of wearable keywords will be useful for understanding the wearable trend and future direction.

• Review of KIISC
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• v.17 no.3
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• pp.60-69
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• 2007

DRM은 단순 보안 기술이 아니라 디지털 콘텐츠의 불법 유통과 복제 방지 및 불법 사용자의 콘텐츠 사용 차단, 지불, 결제 등이 결합한 과금 서비스 등이 결합된 보다 포괄적인 개념의 기술입니다. DRM을 적응하는데 있어서, 온라인 콘텐츠 저작자, 포털이나 이동통신사 등의 저작인접권자, 콘텐츠 소비자, MP3 플래이어나 PMP 등의 재생기기 제작자, 심지어 DRM 솔루션 개발회사 등 많은 이해 관계자들의 이해관계가 얽히게 되며, 따라서 DRM 현황을 이해하고 이슈들을 다루기 위해서는 현재의 비즈니스적인 현황과 기술적인 현황을 함께 고려할 필요성이 있습니다. 또한, 특정 유형의 콘텐츠, 예를 들어 온라인 음악 mp3 파일에 적용된 DRM 현황을 이해하는데 있어서, 다른 콘텐츠에서는 볼 수 없는 해당 콘텐츠 만의 시장 상황과 기술적인 요소들을 좀 더 세부적으로 다룰 필요성이 있습니다. 본 논문에서는 '온라인 음악 콘텐츠 DRM의 비호환'이라는 한정된 주제를 가지고 이에 대한 시장 현황, DRM 적용 현황 및 문제점, 기술 접근 유형 등에 대한 분석을 종합적으로 다루고자 합니다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.525-529
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• 2010

최근 많은 컴퓨팅 작업들이 모바일로 옮겨지기 시작하면서 존재하는 알고리즘을 하드웨어에 구현하여 속도를 높이는 것이 이슈가 되고 있다. 그 중 영상의 특징 점을 기반으로 두 개 이상의 영상을 매칭하는 기술을 중심으로 하는 기술이 다양한 분야에서 연구되고 있다. 본 논문에서는 다양한 분야에서 널리 활용되는 Scale Invariant Feature Transform(SIFT)라는 특징 점 추출 알고리즘의 성능을 분석하여 모바일 디바이스를 위한 비용대비 성능이 높은 최적의 매개변수를 찾는다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.194-196
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• 2019

본 연구에서는 재난문자에 대한 뉴스양과 주요 이슈에 대해 알아보았다. 뉴스 빅데이터 서비스인 빅카인즈를 통해 분석을 실시한 결과, '재난문자' 관련 뉴스가 2016년에 186건으로 전년대비 약 18.6배 증가하는 급격한 성장세를 보였다. 이후 '재난문자' 관련 뉴스는 높은 수치를 유지하는 것으로 나타났다. 지진이 다른 재난에 비해 많은 비중을 차지하였지만 지진이 다수를 차지한 2016년 대비 2017년과 2018년은 지진 외에 다양한 재난에 대해 다루어졌다. 그리고 '재난문자' 연관어 중 행정안전부(국가안전처, 행안부 용어 포함)가 가장 비중 있게 다루어졌고, 기상청과 국민도 비중 있게 다루어진 용어로 나타났다.

• The Journal of Korean Association of Computer Education
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• v.22 no.4
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• pp.21-34
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• 2019

SW education is being implemented in all the school due to the application of the 2015 Curriculum. The purpose of SW education is to improve Computational Thinking by using Unplugged Activities, Educational Programming Language, and Physical Computing. Among them, 73 domestic and 85 overseas researches related to 'Unplugged Activities' were compared and analyzed using semantic network analysis techniques. As a result, the research on 'Unplugged Activities' has been started from 1998, and the research has started in Korea since 2006. As the CT is recognized as a core competence for the future society in line with the 4th Industrial Revolution, researches have been rapidly increasing in both the domestic and overseas countries since 2016. In Korean studies, it was analyzed that many main words related to the elemental factors such as 'unplugged activity', 'robot utilization', 'educational programming language' were found. This suggests that future research should move toward research for the promotion of 'CT' which is the purpose of computer science.