• 한국측량학회지
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• 제34권2호
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• pp.207-215
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• 2016

The demand for spatial data service technologies is increasing lately with the development of realistic 3D spatial information services and ICT (Information and Communication Technology). Research is being conducted on the real-time provision of spatial data services through a variety of mobile and Web-based contents. Big data or cloud computing can be presented as alternatives to the construction of spatial data for the effective use of large volumes of data. In this paper, the process of building HLM (Hyper Live Map) using multi-source data to acquire stereo CCTV and other various data is presented and a big data service architecture design is proposed for the use of flexible and scalable cloud computing to handle big data created by users through such media as social network services and black boxes. The provision of spatial data services in real time using big data and cloud computing will enable us to implement navigation systems, vehicle augmented reality, real-time 3D spatial information, and single picture based positioning above the single GPS level using low-cost image-based position recognition technology in the future. Furthermore, Big Data and Cloud Computing are also used for data collection and provision in U-City and Smart-City environment as well, and the big data service architecture will provide users with information in real time.

• 농촌계획
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• 제25권3호
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• pp.11-18
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• 2019

It is widely known that agricultural plastic waste incineration by farmers may cause big forest fire or fine dust in rural areas. Hence, how to increase the rate of collection and recycling of the agricultural plastic waste is of concern to policy makers especially for rural environment. The purpose of this study is to find the determinants of the collection rate of agricultural plastic waste. This study used the data from 'Research on Agricultural Waste' by the Korea Environment Corporation from year 2012 to 2015 for 163 regions. This study found that the compensation rate for collection, the frequency of collecting services, and the quality of waste are important to increase the collection rate. And the regions with more elderly and low income people are more likely to have higher collection rate. Finally, the chief producing regions that are specialized in a certain crop shows higher collection rate.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.664-666
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• 2014

최근 사용자들에게 다양한 정보를 제공하기 위해 무의미한 데이터를 수집하고 관계를 분석하여 의미 있는 데이터를 추출하는 빅데이터가 이슈이다. 하지만 기존의 데이터 수집 방식은 건물 내 외부에 설치된 센서 및 기타 사용자들의 정보들을 이용하여 데이터를 분석하기 때문에 정보취합에 어려움이 존재한다. 본 논문에서는 이러한 데이터 수집의 문제점을 해결하기 위해 스마트 폰을 이용한 데이터 수집 어플리케이션을 개발한다. 개발하는 데이터 수집 어플리케이션은 Wi-Fi에 대한 정보 및 온도, 습도, 가속도, 자이로 등의 데이터를 측정하며, 웹을 통해 서버로 전송한다. 전송된 데이터는 사용자의 상황 추론을 위한 데이터로써 사용되며, 향후 추론 결과에 따라 사용자의 상황에 맞춰 다양한 서비스의 제공이 가능하다.

• 한국의상디자인학회지
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• 제25권1호
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• pp.83-96
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• 2023

The purpose of this study is to compare and analyze the perception of retro fashion and new-tro fashion using big data. TEXTOM allowed the collection of big data on the words 'retro fashion' and 'new-tro fashion', which was refined afterwards. As for the data collection period, Jan. 1, 2019 to Nov. 30, 2022 was set. A top 50 list of words were extracted from this data based on appearance frequency. The extracted words were processed through Network centrality analysis and CONCOR analysis using Ucinet 6. The results are as follows. 1) In retro fashion, the appearance frequency of 'style' was the highest, followed by 'sensibility', 'color', 'trend', 'fashion', and 'brand'. These words came up with high TF-IDF values. Network centrality analysis discovered that 'color', 'style', 'trend', 'sensibility', and 'design' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; trends, styles, looks, and photos. 2) In new-tro fashion, the appearance frequency of 'retro' was the highest, followed by 'trend', 'generation', 'style', 'brand', and 'fashion'. These words also came up with high TF-IDF values. Network centrality analysis found that 'retro', 'trend', 'generation', and 'brand' had high level of connectivity with other words. CONCOR analysis showed a total of four significant groups; style, brand, clothing, and trend. 3) New-tro fashion is included in retro fashion in that it reproduces the styles of the past. However, it is taken completely differently from generation to generation. Unlike the older generations, millennials actively accept newly created clothes and brands based on the past styles. They perceive it as a fashion that reveals their own unique tastes and tastes.

• Journal of Multimedia Information System
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• 제8권4호
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• pp.301-308
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• 2021

The purpose of this study is to analyze the oral records of sports development contributors to explore the direction of big data research on sports development contributors in the future. To this end, the audio file produced in the interview with Lee00, a sports development contributor, was converted into text. The major themes were extracted by analyzing these oral records. The sub-themes were extracted in chronological order. Keywords were extracted by analyzing sub-themes. And the extracted keywords are searched in Google search engine to find related topics and to use them. A Google search for the topic 'Mt. Inwang' extracted from the oral archives of Lee00, a contributor to the development of sports, finds newspaper articles about President Moon Jae-in's climbing Mt. Inwang and opening up Mt. Bukhan. In addition, articles about Mt. Inwang and mountain climbers that the narrator In-jeong Lee speaks are searched for. Through these articles, you can Deriving the theme of the museum exhibition, Collection of museum exhibits, Use as climbing education material.

• 한국의류산업학회지
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• 제22권5호
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• pp.639-649
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• 2020

This study investigates consumer opinions of clothing care and provides fundamental data to decision-making for oncoming development of clothing care system. Textom, a web-matrix program, was used to analyze big data collected from Naver and Daum with a keyword of "clothing care" from March 2019 to February 2020. A total of 22, 187 texts were shown from the big data collection. Collected big data were analyzed using text-mining, network, and CONCOR analysis. The results of this study were as follows. First, many keywords related to clothing care were shown from the result of frequency analysis such as style, Dryer, LG Electronics, Product, Customer, Clothing, and Styler. Consumers were well recognizing and having an interest in recent information related to the clothing care system. Second, various keywords such as product, function, brand, and performance, were linked to each other which were fundamentally related to the clothing care. The interest in products of the clothing care system were linked to product brands that were also naturally linked to consumer interest. Third, the keywords in the network showed similar attributes from the result of CONCOR analysis that were classified into 4 groups such as the characteristics of purchase, product, performance, and interest. Lastly, positive emotions including goodwill, interest, and joy on the clothing care system were strongly expressed from the result of the sentimental analysis.

• International Journal of Internet, Broadcasting and Communication
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• 제14권2호
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• pp.98-108
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• 2022

In this study, social network analysis was performed to compare and analyze changes in domestic tourism trends before and after the outbreak of COVID-19 in a situation where the damage to the tourism industry due to COVID-19 is increasing. Using Textom, a big data analysis service, data were collected using the keywords "travel destination" and "travel trend" based on the collection period of 2019 and 2020, when the epidemic spread to the world and became chaotic. After extracting a total of 80 key words through text mining, centrality was analyzed using NetDraw of Ucinet6, and clustered into 4 groups through CONCOR analysis. Through this, we compared and analyzed changes in domestic tourism trends before and after the outbreak of COVID-19, and it is judged to provide basic data for tourism marketing strategies and tourism product development in the post-COVID-19.

• 한국멀티미디어학회논문지
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• 제23권10호
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• pp.1286-1295
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• 2020

It has been increasingly difficult to predict the amounts of Acer mono sap to be collected due to droughts and cold waves caused by recent climate changes with few studies conducted on the prediction of its collection volume. This study thus set out to propose a Big Data prediction system based on meteorological information for the collection of Acer mono sap. The proposed system would analyze collected data and provide managers with a statistical chart of prediction values regarding climate factors to affect the amounts of Acer mono sap to be collected, thus enabling efficient work. It was designed based on Hadoop for data collection, treatment and analysis. The study also analyzed and proposed an optimal prediction model for climate conditions to influence the volume of Acer mono sap to be collected by applying a multiple regression analysis model based on Hadoop and Mahout.

• 한국정보통신학회논문지
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• 제21권12호
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• pp.2305-2311
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• 2017

최근들어 공공 정보화와 함께 정부기관, 지자체 및 다양한 정부산하기관에서 보유하고 있는 데이터를 공개하고 있는 추세이다. 즉, 공공기관이 업무수행의 결과물로 생성 및 수집한 다양한 전자화된 형태의 데이터를 공공데이터 포털사이트에서 개방하고 있다. 하지만 이를 사용하는 사용자는 데이터 형식의 이해와 데이터 처리 지식의 부족, 데이터에 대한 접근과 관리의 어려움, 수집 및 저장한 데이터의 이해를 위한 시각화 기술의 부족 등으로 빅데이터의 활용에 제한을 받고 있다. 따라서 본 연구에서는 다양한 공공 사이트에서 제공하는 빅데이터를 데이터셋의 URL 및 API를 사용하여 데이터 포맷에 관계없이 데이터를 수집하며, 수집된 데이터를 XML 구조를 이용하여 재가공하여 데이터베이스화하며, 데이터 융합을 통한 시각화가 가능하도록 하는 공공 빅데이터 수집, 선별 저장 및 시각화 플랫폼을 제안한다.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.297-307
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• 2021

In the vibrant environment, documentation and managing systems are maintained autonomously through education foundations, book materials and libraries at the same time as information are not voluntarily accessible in a centralized location. At the moment Libraries are providing online resources and services for education activities. Moreover, libraries are applying outlets of social media such as Facebook as well as Instagrams to preview their services and procedures. Librarians with the assistance of promising tools and technology like analytics software are capable to accumulate more online information, analyse them for incorporating worth to their services. Thus Libraries can employ big data to construct enhanced decisions concerning collection developments, updating public spaces and tracking the purpose of library book materials. Big data is being produced due to library digitations and this has forced restrictions to academicians, researchers and policy creator's efforts in enhancing the quality and effectiveness. Accordingly, helping the library clients with research articles and book materials that are in line with the users interest is a big challenge and dispute based on Taibah university in Saudi Arabia. The issues of this domain brings the numerous sources of data from various institutions and sources into single place in real time which can be time consuming. The most important aim is to reduce the time that lapses among the authentic book reading and searching the specific study material.