• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.119-125
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• 2019

The purpose of this study is to find out the relevant factors of the choice tendency of tourism users to Intelligent Tourism platform through big data analysis, which will help enterprises to make accurate positioning and improvement according to user information feedback in the tourism market in the future, so as to gain the favor of users' choice and achieve long-term market competitiveness. This study takes the Intelligent Tourism platform as the independent variable and the user choice tendency as the dependent variable, and explores the related factors between the Intelligent Tourism platform and the user choice tendency. This study make use of text mining and R language text analysis, and uses SPSS and AMOS statistical analysis tools to carry out empirical analysis. According to the analysis results, the conclusions are as follows: service quality has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with tourism trust; Tourism Trust has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with user experience; user experience has a significant positive correlation with user choice tendency Positive correlation effect.

• Journal of Korea Multimedia Society
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• v.18 no.8
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• pp.925-934
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• 2015

The frequency of natural disasters because of global warming is gradually increasing, risks of flooding due to typhoon and torrential rain have also increased. Among these causes, the roads are flooded by suddenly torrential rain, and then vehicle and personal injury are happening. In this respect, because of the possibility that immersion of a road may occur in a second, it is necessary to study the rapid data collection and quick response system. Our research proposes a big data analysis system based on the collected information and a variety of system information collection methods for searching flooded road areas by torrential rains. The data related flooded roads are utilized the SNS data, meteorological data and the road link data, etc. And the big data analysis system is implemented the distributed processing system based on the Hadoop platform.

• Journal of KIBIM
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• v.10 no.4
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• pp.11-21
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• 2020

With increasing interest and research on smart cities, there is also an increasing number of studies on urban facilities that can be built within smart cities. According to these studies, smart cities' urban facilities are likely to become high value-added industries. However, the concept of smart city is not clear because it involves various fields. Therefore, in this study, the definition of Next-Generation(N.G) Smart City Facilities with Digital Twin and Digital Chain is carried out through a multidisciplinary approach. Based on this, Next-Generation Smart City Facilities will be divided into High Value-Added Products and Big Data Platforms. Subsequently, the definition of the Digital Chain containing the data flow of the entire process built through the construction of the Digital Twin proceeds. The definitions derived are applied to the Next-Generation Noise Barrier Tunnel to ensure that data is exchanged at the Digital Twin stage, and to review the proposed configuration of the Digital Chain and Data Flow in this study. The platform definition and Digital Chain of Next-Generation Smart City Facilities proposed in this study suggest that it can affect not only the aspects of data management that are currently in the spotlight, but also the manufacturing industry as a whole.

• Knowledge Management Research
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• v.19 no.1
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• pp.119-132
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• 2018

Many advanced products and services are emerging in the market thanks to data-based technologies such as Internet (IoT), Big Data, and AI. The construction of a system for data processing under the IoT network environment is not simple in configuration, and has a lot of restrictions due to a high cost for constructing a high performance server environment. Therefore, in this paper, we will design a development environment for large data analysis computing platform using open source with low cost and practicality. Therefore, this study intends to implement a big data processing system using Raspberry Pi, an ultra-small PC environment, and open source API. This big data processing system includes building a portable server system, building a web server for web mining, developing Python IDE classes for crawling, and developing R Libraries for NLP and visualization. Through this research, we will develop a web environment that can control real-time data collection and analysis of web media in a mobile environment and present it as a curriculum for non-IT specialists.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.158-168
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• 2024

With Wenhai big data SaaS cloud platform.2.0, this study analyzed data of 135 news reports relating to Chinese city Chongqing from Yonhap News Agency and ten South Korean mainstream newspapers from May 1^st, 2018 to September 30^th, 2022. Under the framework of Frame Theory, this research conducted data mining and analysis on how Korean mainstream media shaped city image of Chongqing, what kind of city images were shaped from dimensions of politics, economy, society, culture & sports as well as tourism and whether they are consistent with those in Chinese media. At the last part, discussions and suggestions was made.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1399-1410
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• 2015

Gartner is requiring companies to considerably change their survival paradigms insisting that companies need to understand and provide again the upcoming era of data competition. With the revealing of successful business cases through statistic algorithm-based predictive analytics, also, the conversion into preemptive countermeasure through predictive analysis from follow-up action through data analysis in the past is becoming a necessity of leading enterprises. This trend is influencing security analysis and log analysis and in reality, the cases regarding the application of the big data analysis framework to large-scale log analysis and intelligent and long-term security analysis are being reported file by file. But all the functions and techniques required for a big data log analysis system cannot be accommodated in a Hadoop-based big data platform, so independent platform-based big data log analysis products are still being provided to the market. This paper aims to suggest a framework, which is equipped with a real-time and non-real-time predictive analysis engine for these independent big data log analysis systems and can cope with cyber attack preemptively.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• The Journal of Small Business Innovation
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• v.20 no.3
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• pp.49-68
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• 2017

Platform finance is emerging as an alternative finance for SMEs by suggesting a new funding source based on a new technology named FinTech. The essence of this business is the adapting ICT challenges to the financial industry that can adequately reflect risk assessment using Big Data and effectively meet individual risk-return preference. Thus, this is evolving as an alternative to existing finance in the form of P2P loans for Micro Enterprises and supply-chain finance for SMEs that need more working capital. Platform finance in Korea, however, is still at an infant stage and requires policy support. This can be summarized as follows: "Participation of institutional investors and the public sector," meaning that public investors provide seed money for the private investors to crowd in for platform finance. "Negative system in financial regulations," with current regulations to be deferred for new projects, such as Sandbox in the UK. In addition, "Environment for generous use of data," allowing discretionary data sharing for new products," and "Spreading alternative investments," fostering platform finance products as alternative investments in the low interest-rate era.

• KNOM Review
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• v.22 no.2
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• pp.12-21
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• 2019

There is a rapid development of experimental equipment and ICT technology in data-intensive scientific areas, thus, big data of more than exabyte size is being generated. However, the big data transmission technology does not satisfy the needs of the application researchers who utilize it. Various high-performance transmission technologies have been developed based on QoS(Quality of Service), but they also require changes in the clean slate method. On the other hand, ScienceDMZ technologies improve the performance of scientific big data transmission by bypassing the firewall that causes a big problem in transmission performance. In addition, it is possible to implement without changing the existing network. In this paper, we built ScienceDMZ in an international long-distance environment based on KREONET(Korea Research Environment Open NETwork), and we verified the performance. We also introduced how GPU platform could be linked in a distributed ScienceDMZ environment.