• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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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.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.3
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• pp.47-57
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• 2022

This study attempted to grasp the status and perception of Uljin Geumgangsong by grasping mass media issues and user perception using big data, and to present basic data when constructing monitoring using user perception by examining the establishment relationship of agenda setting from a time-series perspective. The results of collecting and analyzing text data that can identify mass media and visitor awareness are as follows. First, both mass media and visitor keywords were related to the importance of the value and meaning of Uljin Geumgangsong. Second, in the case of the connection network, Geumgang Pine Agriculture was centered, but in the case of difference in perception between mass media and visitors, such results were derived due to the object of interest. Third, in the case of the connection relationship structure, the connection strength was strong because there were many overlapping contents of mass media. Fourth, as a result of the centrality analysis, both mass media and visitor-aware keywords were positively recognized as spaces created and maintained through institutional support, and objective perception could be grasped by finding hidden keywords. Fifth, as a result of time series analysis, it was possible to grasp the flow through the issue keywords that appeared by period, and unlike the past, it was recognized as a place for tourism and travel. Finally, as a result of examining whether the agenda setting is consistent, there is a mass media influence, so it is thought that more diverse and more information and publicity are needed by utilizing it.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.173-183
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• 2019

This study aims to utilize big data contents of news and social media for developing a corporate strategy of multinational enterprises and their global decision-making through the data mining technique, especially text mining. In this paper, the data of 2 news media (BBC and CNN) and 2 social media (Facebook and Twitter) were collected for the three global leading Korean companies (Samsung, Hyundai Motor Company, and LG) from April, 2018 to April, 2019. The findings of this paper have shown that traditional news media and also modern social media have become devastating tools to extract global trends or phenomena for businesses. Moreover, this presents that a company can adopt a two-track strategy through two different types of media by deriving the key issues or trends from news media channels and also grasping consumers' sentiments, preference or issues of interest such as battery or design from social media. In addition, analyzing the texts of those media and understanding the association rules greatly contribute to the comparison between two different types of media channels to see the difference. Lastly, this provides meaningful and valuable data empowered insights to find a future direction comprehensively and develop a global strategy for sustainability of business.

• Asian Journal for Public Opinion Research
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• v.8 no.3
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• pp.393-406
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• 2020

The discourse on the lockdown in Indonesia is getting stronger due to the increasing number of positive cases of the coronavirus and the death rate. As of August 12, 2020, the confirmed number of COVID-19 cases in Indonesia reached 130,718. There were 85,798 victims who have recovered and 5,903 who have died. Data show a significant increase in cases of COVID-19 every day. For this reason, there needs to be an evaluation of the government policy of the Republic of Indonesia in dealing with the COVID-19 pandemic in Indonesia. An evaluation of policies for handling the pandemic must include public opinion to determine any weaknesses of this policy. The development of public opinion about the lockdown policy can be understood through social media. During the COVID-19 pandemic, measuring public opinion through traditional methods (surveys) was difficult. For this reason, we utilized big data on social media as research data. The main purpose of this study is to understand public opinion on the lockdown policy in overcoming the COVID-19 pandemic in Indonesia. The things observed included: volume of Twitter users, top influencers, top tweets, and communication networks between Twitter users. For the methodological development of future public opinion research, the researchers outline the obstacles faced in researching public opinion based on big data from Twitter. The research results show that the lockdown policy is an interesting issue, as evidenced by the number of active users (79,502) forming 133,209 networks. Posts about the lockdown on Twitter continued to increase after the implementation of the lockdown policy on April 10, 2020. The lockdown policy has caused various reactions, seen from the word analysis showing 14.8% positive sentiment, 17.5% negative, and 67.67% non-categorized words. Sources of information who have played the roles of top influencers regarding the lockdown policy include: Jokowi (the president of the Republic of Indonesia), online media, television media, government departments, and governors. Based on the analysis of the network structure, it shows that Jokowi has a central role in controlling the lockdown policy. Several challenges were found in this study: 1) choosing keywords for downloading data, 2) categorizing words containing public opinion sentiment, and 3) determining the sample size.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.183-188
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• 2020

This study is primarily aimed at providing a foundation for academic development and the leap forward of the Special Security Industry through the press report analysis on Korea's special security guard using big data. The research methods It was analyzed by the research methods in relation to keyword trends for 'special security guard' and 'special guards' using the Big Kinds program. According to the analysis based on the period of growth (quantitative and qualitative) of the special security industry, there were many press reports and exposure related to carrying firearms, national major facilities, and regular employees. Unlike the general security guards, the special security guards were released higher by media as a law was revised to allow them to carry or use firearms at important national facilities. There was a lot of media attention concerned about the side effects of misuse, and there were also high media reports on the transition of regular workers to improve poor treatment, such as the unstable status of special security guards and low wages. Therefore, the need for continuous development and improvement of professionalism and work efficiency of special security services are emphasized.

• Journal of People, Plants, and Environment
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• v.22 no.5
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• pp.455-466
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• 2019

This study was carried out to analyze trends in floral products and services through the big data analysis of various social networking services (SNSs) and then to provide objective marketing directions for the floricultural industry. To analyze the big data of SNSs, we used four analytical methods: Cotton Trend (Social Matrix), Naver Big Data Lab, Instagram Big Data Analysis, and YouTube Big Data Analysis. The results of the big data analysis showed that SNS users paid positive attention to flower one-day classes that can satisfy their needs for direct experiences. Consumers of floral products and services had their favorite designs in mind and purchased floral products very actively. The demand for flower items such as bouquets, wreaths, flower baskets, large bouquets, orchids, flower boxes, wedding bouquets, and potted plants was very high, and cut flowers such as roses, tulips, and freesia were most popular as of June 1, 2019. By gender of consumers, females (68%) purchased more flower products through SNSs than males (32%). Consumers preferred mobile devices (90%) for online access compared to personal computers (PCs; 10%) and frequently searched flower-related words from February to May for the past three years from 2016 to 2018. In the aspect of design, they preferred natural style to formal style. In conclusion, future marketing activities in the floricultural industry need to be focused on social networks based on the results of big data analysis of popular SNSs. Florists need to provide consumers with the floricultural products and services that meet the trends and to blend them with their own sensitivity. It is also needed to select SNS media suitable for each gender and age group and to apply effective marketing methods to each target.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.15-23
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• 2015

This thesis proposes how data security has changed since the emergence of 'Big Data' in 2012 and the type of Integrated Security Management System that needs to be built against security threats, based on an analysis of Big Data. Much research has been conducted in Big Data. I need to think about what an Integrated Security Management System requires in order to safeguard against security threats such as APT. I would like to draw a comparison between the current Integrated Security Management System and one that is based on Big Data, including its limitations and improvements, so that I can suggest a much improved version of Integrated Security Management System.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.399-400
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• 2018

해마다 방대한 양의 콘텐츠가 쏟아져 나오는 현재의 콘텐츠 시장은 '즐길 거리'가 차고 넘치는, 수요보다 공급이 많은 시장이다. 이러한 환경에서 소비자가 자신의 취향에 맞는 콘텐츠를 쉽고 빠르게 찾을 수 있게 하는 맞춤형 콘텐츠 제공의 측면에서 빅데이터의 효율적인 활용은 중요하다. 더 나아가 콘텐츠의 소비 단계 뿐만 아니라 기획 및 제작 단계에서도 빅데이터는 소비자가 흥미를 느낄만한 콘텐츠를 미리 예측하며, 성공 가능성 높은 콘텐츠를 기획 및 제작할 수 있게 하는데 기인하는 중요한 핵심 요소이다. 이미 게임, 영상, 음악 등의 분야에서는 개인의 기호와 취향에 맞춤화된 콘텐츠를 제공하거나 소비자에게 더 인기를 얻을 수 있는 콘텐츠 기획 및 개발에 빅데이터를 활용하고 있으며, 앞으로는 더욱 다양한 장르에서 빅데이터 활용 사례가 증가할 전망이다.

• Smart Media Journal
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• v.6 no.3
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• pp.83-88
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• 2017

The data analysis system using Big-data is worthy to be used in various fields such as politics, traffic, natural disaster, shopping, customer management, medical care, and weather information. Particularly, the analysis of the momentum of an individual using an acceleration signal collected from a wearable device has already been widely used. However, since the data used in such a system stores only the data necessary for measuring the individual activity, it does not provide various analysis results other than the exercise amount of the individual. In this paper, I propose a system that analyzes collective behavior pattern and activity based on the acceleration signal that can be collected from personal smartphones for 24 hours a day and stored in big data. I also propose a system that sends acceleration signals and receives analysis results using standard messaging to use on various smart devices.