• Title/Summary/Keyword: Big Data Application

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Design of a Smart Application using Big Data (빅 데이터를 이용한 스마트 응용의 설계)

  • Oh, Sun-Jin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.6
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    • pp.17-24
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    • 2015
  • With the rapid growth of Information technology and up-to-date wireless network application technologies, huge and various types of data are produced in every moment, the value and significance of the analysis techniques using big data are increased recently. Big data, which were useless since they were too huge to manage in the past, enables us to get new inspirations and values in various practical application areas through the development of big data computing devices and analytic tools. Nowadays, however, it is true that most of the big data are still wasted without properly analyzed and used. In the long run, the preliminary stipulations for finding inspirations and extracting new values from big data are securing big data analysis and application techniques to process big data efficiently. In this paper, we study accurate data analysis techniques and data process technologies those are able to extract needed inspirations and values from big data efficiently, then design the smart application that adopts these techniques practically.

Utilizing Spatial Big Data for Land and Housing Sector (토지주택분야 정보 현황과 빅데이터 연계활용 방안)

  • Jeong, Yeun-Woo;Yu, Jong-Hun
    • Land and Housing Review
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    • v.7 no.1
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    • pp.19-29
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    • 2016
  • This study proposes the big data policy and case studies in Korea and the application of land and housing of spatial big data to excavate the future business and to propose the spatial big data based application for the government policy in advance. As a result, at first, the policy and cases of big data in Korea were evaluated. Centered on the Government 3.0 Committee, the information from each department of government is being established with the big-data-based system, and the Ministry of Land, Infrastructure, and Transport is establishing the spatial big data system from 2013 to support application of big data through the platform of national spatial information and job creation. Second, based on the information system established and administrated by LH, the status of national territory information and the application of land and housing were evaluated. First of all, the information system is categorized mainly into the support of public ministration, statistical view, real estate information, on-line petition, and national policy support, and as a basic direction of major application, the national territory information (DB), demand of application (scope of work), and profit creation (business model) were regarded. After the settings of such basic direction, as a result of evaluating an approach in terms of work scope and work procedure, the four application fields were extracted: selection of candidate land for regional development business, administration and operation of rental house, settings of priority for land preservation, and settings of priority for urban generation. Third, to implement the application system of spatial big data in the four fields extracted, the required data and application and analytic procedures for each application field were proposed, and to implement the application solution of spatial big data, the improvement and future direction of evaluation required from LH were proposed.

The Analyzing Risk Factor of Big Data : Big Data Processing Perspective (빅데이터 처리 프로세스에 따른 빅데이터 위험요인 분석)

  • Lee, Ji-Eun;Kim, Chang-Jae;Lee, Nam-Yong
    • Journal of Information Technology Services
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    • v.13 no.2
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    • pp.185-194
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    • 2014
  • Recently, as value for practical use of big data is evaluated, companies and organizations that create benefit and profit are gradually increasing with application of big data. But specifical and theoretical study about possible risk factors as introduction of big data is not being conducted. Accordingly, the study extracts the possible risk factors as introduction of big data based on literature reviews and classifies according to big data processing, data collection, data storage, data analysis, analysis data visualization and application. Also, the risk factors have order of priority according to the degree of risk from the survey of experts. This study will make a chance that can avoid risks by bid data processing and preparation for risks in order of dangerous grades of risk.

Analysis on Major Factors for Analysis & Application of Big Data in Electrical Commercial System (전자상거래 시스템에서 빅 데이터의 분석 및 결과 활용에 미치는 영향요소 분석)

  • Yang, Hoo-Youl;Na, Cheol-Hun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.373-375
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    • 2016
  • Analyze the Big Data become a hot issue because of Smart environment, the amount of data in the world has been exploding. Result of application makes a good use of Analysis and applicate of the big data, is play an important part in application area (finance, circulation, manufacturing, disaster etc.) This paper presents an influence element for data analysis and its practical use based in result of maturity in Business process of Big Data in Electrical Commercial system.

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An Exploratory Study on Application Plan of Big Data to Manufacturing Execution System (제조실행시스템에의 빅데이터 적용방안에 대한 탐색적 연구)

  • Noh, Kyoo-Sung;Park, Sanghwi
    • Journal of Digital Convergence
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    • v.12 no.1
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    • pp.305-311
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    • 2014
  • The manufacturing industry early have been introducing automation and information systems of the engineering and production process for getting competitive advantage. one of the typical information systems is MES(Manufacturing Execution System) and it keeps evolving. As Big Data showed up nowadays, application method of Big Data to MES is also being sought. First, this study will do preceding research and cases study on the application of Big Data in the manufacturing industry. Then, it will suggest application Plan of Big Data to MES.

A review of big data analytics and healthcare (빅데이터 분석과 헬스케어에 대한 동향)

  • Moon, Seok-Jae;Lee, Namju
    • Journal of the Korean Applied Science and Technology
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    • v.37 no.1
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    • pp.76-82
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    • 2020
  • Big data analysis in healthcare research seems to be a necessary strategy for the convergence of sports science and technology in the era of the Fourth Industrial Revolution. The purpose of this study is to provide the basic review to secure the diversity of big data and healthcare convergence by discussing the concept, analysis method, and application examples of big data and by exploring the application. Text mining, data mining, opinion mining, process mining, cluster analysis, and social network analysis is currently used. Identifying high-risk factor for a certain condition, determining specific health determinants for diseases, monitoring bio signals, predicting diseases, providing training and treatments, and analyzing healthcare measurements would be possible via big data analysis. As a further work, the big data characteristics provide very appropriate basis to use promising software platforms for development of applications that can handle big data in healthcare and even more in sports science.

Study on Decision-Making Factors of Big Data Application in Enterprises: Using Company S as an Example

  • Huang, Yun Kuei;Yang, Wen I.;Chan, Ching Sen
    • East Asian Journal of Business Economics (EAJBE)
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    • v.4 no.1
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    • pp.5-15
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    • 2016
  • With vigorous development of global network community, smart phones and mobile devices, enterprises can rapidly collect various kinds of data from internal and external environments. How to discover valuable information and transform it into new business opportunities from big data which grow rapidly is an extremely important issue for current enterprises. This study treats Company S as the subject and tries to find the factors of big data application in enterprises by a modified Decision Making Trial and Evaluation Laboratory (DEMATEL) and perceived benefits - perceived barriers relation matrix as reference for big data application and management of managers or marketing personnel in other organizations or related industry.

A Keyword-Based Big Data Analysis for Individualized Health Activity: Focusing on Methodological Approach

  • Kim, Han-Byul;Bae, Geun-Pyo;Huh, Jun-Ho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.04a
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    • pp.540-543
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    • 2017
  • It will be possible to solve some of the major issues in our society and economy with the emerging Big Data used across 21st century global digital economy. One of the main areas where big data can be quite useful is the medical and health area. IT technology is being used extensively in this area and expected to expand its application field further. However, there is still room for improvement in the usage of Big Data as it is difficult to search unstructured data contained in Big Data and collect statistics for them. This limits wider application of Big Data. Depending on data collection and analysis method, the results from a Big Data can be varied. Some of them could be positive or negative so that it is essential that Big Data should be handled adequately and appropriately adapting to a purpose. Therefore, a Big Data has been constructed in this study to applying Crawling technique for data mining and analyzed with R. Also, the data were visualized for easier recognition and this was effective in developing an individualized health plan from different angles.

Application Analysis of Smart Tourism Management Model under the Background of Big Data and IOT

  • Gangmin Weng;Jingyu Zhang
    • Journal of Information Processing Systems
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    • v.19 no.3
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    • pp.347-354
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    • 2023
  • The rapid development of information technology has accelerated the application of big data and the Internet of Things in various industries. Big data has a great potential in the development of smart tourism. With the help of innovation in emerging technologies such as big data and Internet of Things, smart tourism has a better possibility to surpass traditional tourism. Therefore, this article provides a theoretical support to this process. It has explored the innovative management model of big data and IoT in smart tourism and evaluate their effects on promoting tourism. It offers a reference for the integration and innovation of the tourism theory system. Before big data technology, the development of Internet boosted online tourism. However, tourism marketing is still inefficient due to a lack of understanding about tourists. After many practical explorations of big data technology, tourism websites begin to adopt big data technology in their daily operations. With the changes in tourists' preferences and needs, further innovation and research are needed to help smart tourism keep up with the changes in the market and create more competitive products and services. Innovation serves as the driving force for enterprises to occupy the market and develop.

Correspondence Strategy for Big Data's New Customer Value and Creation of Business (빅 데이터의 새로운 고객 가치와 비즈니스 창출을 위한 대응 전략)

  • Koh, Joon-Cheol;Lee, Hae-Uk;Jeong, Jee-Youn;Kim, Kyung-Sik
    • Journal of the Korea Safety Management & Science
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    • v.14 no.4
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    • pp.229-238
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    • 2012
  • Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.