• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.673-674
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• 2020

의식주 중에서 자신을 표현하고 외부와의 교류를 할 수 있는 분야는 패션분야로서 인간 생활과 밀접한 관계를 가지고 있으며 사람들의 개인화된 성향 변화 및 인터넷 환경의 개선으로 트렌드는 빠르게 변화하고 있다. 인공지능 기술의 발전은 단순히 객체의 검출 및 분류에서 벗어나 패션 아이템의 분석 및 세부적인 속성을 분석할 수 있는 수준에 다다랐으며 인공지능 기술을 활용하여 사용자에게 추천할 수 있는 서비스가 출시되고 있다. 패션 트렌드의 빠른 변화 및 인공지능 기술의 발전으로 이를 활용한 플랫폼에 기반을 두어 디자이너에게는 디자인 기술을 향상시킬 수 있으며 사용자에게는 개인화된 제품을 구매할 수 있는 플랫폼 개발이 요구되고 있다. 본 논문에서는 인공지능 기술 기반 패션 분석 기술 개발을 위하여 패션 검출 모듈, 패션 검색 모듈, 패션 검색을 위한 벡터 검색 모듈, 상하의 분리를 위한 세그먼테이션 모듈, 패션 복종 분류 모듈을 개발하여 통합하였으며 패션 검색 정확도는 Top-5 기준 75.28%, 벡터 검색 속도는 벡터당 0.002m sec 이하, 세그먼테이션 추출 정확도 87.6%이상, 패션 검출 결과 IoU 0.5 환경에서 96.2%, 복종분석 90.54%의 성능을 보였다.

• Journal of Service Research and Studies
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• v.11 no.3
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• pp.43-54
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• 2021

This study focused on indoor spaces and convenience devices among vehicle interior designs suitable for the autonomous driving era, and presented an interior design model for future automobiles by applying the STEEP analysis method. The service design methodology is applied to deal with changes in display devices installed for the purpose of rearranging layouts and providing driver-centered information. Changes in types and installation locations of displays for various purposes such as connected and infotainment are expected. In particular, through this analysis, trends and experiences through indoor interior research in future self-driving cars will be studied, and subsequent studies will be used as basic data for actual development and application. Key drivers were extracted after deriving future trends linking the research project conducted in five stages to STEEP and consulting experts through FGI. Through this, it was later presented as a direction for indoor design. Through user-centered participatory design methods, emotional keyword derivation methods were used, summarized the derived drivers in five major trends in the future society, and each derived drivers were grouped to consider the relevant technology fields, and added elements to the autonomous driving level. This is an indoor ray viewed from the perspective of various social issues as well as personal tendencies in the future self-driving car industry.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.35-45
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• 2012

Researchers and scientists spend huge amount of time in analyzing the previous studies and their results. In order to timely take the advantageous position, they usually analyze various resources such as paper, patents, and Web documents on recent research issues to preoccupy newly emerging technologies. However, it is difficult to select invest-worthy research fields out of huge corpus by using the traditional information search based on keywords and bibliographic information. In this paper, we propose a method for efficient creation, storage, and utilization of semantically relevant information among technologies, products and research agents extracted from 'big data' by using text mining. In order to implement the proposed method, we designed an ontology that creates technological knowledge for semantic web environment based on the relationships extracted by text mining techniques. The ontology was utilized for InSciTe Adaptive, a R&D trends analysis and forecast service which supports the search for the relevant technological knowledge.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.133-136
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• 2013

근래 트위터와 페이스북 등의 SNS(Social Network Service)에서 일반 대중의 관심사나 트렌드 등의 이슈를 탐지하는 많은 연구가 이루어지고 있다. 본 논문에서는 검색어에 대한 연관 어휘 추출을 통해 검색어에 연관된 이슈나 화제를 트위터에서 추출하기 위한 방법을 제안한다. 본 논문에서는 연관성이 높은 단어는 서로 가깝게 발생할 것으로 기대하고, 단어 간 거리가 가까울수록, 공기빈도가 높을수록 커지는 단어연관도 계산법을 제안한다. 연관도 값이 임계치를 넘는 어휘를 연관 어휘로 보고 네트워크의 형태로 관련 이슈를 제시한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.99-100
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• 2020

본 연구는 최근 우리나라 국민들의 주요 관심 교육정책인 '고교학점제' 관련 언론기사들을 한국언론재단의 빅카인즈(BIGKinds) 시스템을 활용하여 분석하였다. 본 연구에서는 2018년 1월 1일부터 2019년 11월 30일까지 기간을 설정한 후, 총 54개 언론사의 '고교학점제' 관련기사들을 추출하였다. 그 다음, 추출된 '고교학점제' 관련 기사들을 대상으로 뉴스트렌드 분석, 네트워크 지도 구현, 핵심어 추출 및 워드클라우드 제시 등의 연구과정을 거쳤다. 본 연구결과는 '고교학점제'의 정책 진행 과정성의 과제 및 쟁점들을 해결하는데 기초자료로 활용될 수 있을 것으로 기대된다.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.38-49
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• 2021

This study analyzed the trend of the term 'false and exaggerated advertisement' in 5,141 newspaper articles from 1990 to 2019 using text mining methodology. First of all, we identified the most frequent keywords of false and exaggerated advertisements through frequency analysis for all newspaper articles, and understood the context between the extracted keywords. Next, to examine how false and exaggerated advertisements have changed, the frequency analysis was performed by separating articles by 10 years, and the tendency of the keyword that became an issue was identified by comparing the number of academic papers on the subject of the highest keywords of each year. Finally, we identified trends in false and exaggerated advertisements based on the detailed keywords in the topic using the topic modeling. In our results, it was confirmed that the topic that became an issue at a specific time was extracted as the frequent keywords, and the keyword trends by period changed in connection with social and environmental factors. This study is meaningful in helping consumers spend wisely by cultivating background knowledge about unfair advertising. Furthermore, it is expected that the core keyword extraction will provide the true purpose of advertising and deliver its implications to companies and related employees who commit misconduct.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.11-19
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• 2012

Due to existing infrastructure to collect traffic information was constructed to expressway and national highway, we cannot precisely know traffic situation for their surrounding area. Therefore, it is difficult to provide reliable traffic information to users using navigation and smartphone. In this research, we collected aerial images by using unmanned airship capable of wide-area monitoring and proposed a method extracting vehicle speed from the collected data. And, we performed experiments to verify the accuracy of extracted vehicle speed. Our method proposed in this research can be used to extract a new approach of traffic information according to increased demand of traffic monitoring. We expect that our method will become a new research trend in traffic information application.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.402-403
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• 2023

본 연구의 목적은 LDA 토픽 모델링을 활용하여 한국어 SNS데이터에 분석을 통해 우리나라의 여가활동, 일과 직업, 주거와 생활의 동향을 살펴보는 것이다. AI Hub에서 제공하는 한국어 SNS데이터를 수집하고 형태소 분석, 전처리 과정을 거친 후 coherence score을 토대로 최적의 토픽 수를 결정하여 토픽을 추출하였다. 도출한 트렌드를 바탕으로 경영, 마케팅 분야에 미치는 영향을 예측할 수 있을 것으로 기대한다.

• Journal of Platform Technology
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• v.11 no.4
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• pp.19-34
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• 2023

In order to identify the trends and insights of 'startups' in the global era, we conducted an in-depth trend analysis of the global startup ecosystem using Google Trends, a big data analysis platform. For the validity of the analysis, we verified the correlation between the keywords 'startup' and 'global' through BIGKinds. We also conducted a network analysis based on the data extracted using Google Trends to determine the frequency of searches for the keyword or term 'startup'. The results showed a strong positive linear relationship between the keywords, indicating a statistically significant correlation (correlation coefficient: +0.8906). When exploring global startup trends using Google Trends, we found a terribly similar linear pattern of increasing and decreasing interest in each country over time, as shown in Figure 4. In particular, startup interest was low in the range of 35 to 76 from mid-2020 due to the COVID-19 pandemic, but there was a noticeable upward trend in startup interest after March 2022. In addition, we found that the interest in startups in each country except South Korea is very similar, and the related topics are startup company, technology, investment, funding, and keyword search terms such as best startup, tech, business, invest, health, and fintech are highly correlated.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.97-109
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• 2024

In the field of domestic tourism, tourism trend analysis of tourism consumers, both international tourists and domestic tourists, is essential not only for the Korean tourism market but also for local and governmental tourism policy makers. e will explore the keywords and sentiment analysis on social media to establish a marketing strategy plan and revitalize the domestic tourism industry through communication and information from tourism consumers. This study utilized TEXTOM 6.0 to analyze recent trends in Korean tourism. Data was collected from September 31, 2022, to August 31, 2023, using 'Korean tourism' and 'domestic tourism' as keywords, targeting blogs, cafes, and news provided by Naver, Daum, and Google. Through text mining, 100 key words and TF-IDF were extracted in order of frequency, and then CONCOR analysis and sentiment analysis were conducted. For Korean tourism keywords, words related to tourist destinations, travel companions and behaviors, tourism motivations and experiences, accommodation types, tourist information, and emotional connections ranked high. The results of the CONCOR analysis were categorized into five clusters related to tourist destinations, tourist information, tourist activities/experiences, tourism motivation/content, and inbound related. Finally, the sentiment analysis showed a high level of positive documents and vocabulary. This study analyzes the rapidly changing trends of Korean tourism through text mining on Korean tourism and is expected to provide meaningful data to promote domestic tourism not only for Koreans but also for foreigners visiting Korea.