• Title/Summary/Keyword: Big data analysis

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The Characteristics of Tools for Big Data Analysis (빅데이터 분석도구의 특성)

  • Kim, Do-Goan;So, Soon-Hu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.114-116
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    • 2016
  • Today, the analysis of big data hae been used as an essential tool for finding customers' needs. Various big-data analysis sites have provided the analysis results with their own forms and styles according to their service and characteristics. Therefore, to use the analysis results for marketing fields, we have to understand the major characteristics on big data analysis tools. In this point, this study attempts to compare the characteristics of big data analysis results and styles from big data analysis sites.

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Big Data Analysis Using Principal Component Analysis (주성분 분석을 이용한 빅데이터 분석)

  • Lee, Seung-Joo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.6
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    • pp.592-599
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    • 2015
  • In big data environment, we need new approach for big data analysis, because the characteristics of big data, such as volume, variety, and velocity, can analyze entire data for inferring population. But traditional methods of statistics were focused on small data called random sample extracted from population. So, the classical analyses based on statistics are not suitable to big data analysis. To solve this problem, we propose an approach to efficient big data analysis. In this paper, we consider a big data analysis using principal component analysis, which is popular method in multivariate statistics. To verify the performance of our research, we carry out diverse simulation studies.

A Big Data Analysis of Yumentingzheng: Weiwenqiju as an Example (어문청정 빅데이터 분석: 위문기거 일례)

  • Snowberger, Aaron Daniel;Lee, Choong Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.624-626
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    • 2021
  • Yumentingzheng, which records the contents of the Qing dynasty's discussions with his subjects, is an important document like the Annals of Joseon in Korea. This paper describes the method and steps for big data analysis of Yumentingzheng written in Manchu alphabet. In big data analysis of documents written in Manchu characters, there are many problems that need to be solved in advance, and research on these should be preceded. In this paper, a method of big data analysis using the R language was proposed in the stage where the text written in Manchurian characters was transliterated into Latin characters through a preliminary study to be conducted in the future. In the proposed method, Apkai method was adopted for the transliteration of Wumentingzheng, and the results of big data analysis were presented using the text of Weiwenqiju.

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A Study on MIS Curriculum and NCS-based Big Data Analysis Job Competency Using Keyword Network Analysis (키워드 네트워크 분석을 이용한 MIS 교과정보와 NCS 기반 빅데이터 분석 직무역량에 대한 연구)

  • Lee, Taewon;Sung, Haengnam;Kim, Eun-Jung
    • The Journal of Information Systems
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    • v.29 no.4
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    • pp.101-121
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    • 2020
  • Purpose The purpose of this study is to understand the current status of MIS curriculum and to find ways to improve it. In addition, the results of the research can be used as basic data for improving MIS curriculum. Design/methodology/approach A research framework was designed to derive research results using the keyword network analysis method of this study: 1) Keywords were extracted based on the six units of the big data analysis job competency. 2) And based on the extracted keywords, the relationship between the keywords and MIS curriculum for each university was identified. Findings In the MIS curriculum information of a few universities, education related to big data analysis was conducted. 1) In the MIS curriculum of a few universities, education related to big data analysis was conducted. However, MIS curriculum of the university, which is the subject of analysis, education focused on concepts and theory rather than practical education was conducted. 2) And it was confirmed that there is a difference from the education required by the industry.

A Study on the Big Data Analysis System for Searching of the Flooded Road Areas (도로 침수영역의 탐색을 위한 빅데이터 분석 시스템 연구)

  • Song, Youngmi;Kim, Chang Soo
    • 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.

Developing a Big Data Analysis Platform for Small and Medium-Sized Enterprises

  • Kim, Hyeon Gyu
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.8
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    • pp.65-72
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    • 2020
  • Big data analysis is widely used in applications such as finance and communication, whose market size is growing rapidly every year. Nevertheless, it is rarely used by SMEs (small and medium-sized enterprises) since the existing services are not fully customized for them while being offered at high price. To resolve this, we develop and propose a new platform to provide big data analysis services specialized for SMEs in this paper. First, we compare existing work discussing social big data analysis, and extract service features necessary to help their marketing effectively. Then, we present a prototype system implementing the extracted features, and discuss technical issues needed to develop a complete system which are obtained from the prototype implementation.

Big Data Smoothing and Outlier Removal for Patent Big Data Analysis

  • Choi, JunHyeog;Jun, Sunghae
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.8
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    • pp.77-84
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    • 2016
  • In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

Offline-to-Online Service and Big Data Analysis for End-to-end Freight Management System

  • Selvaraj, Suganya;Kim, Hanjun;Choi, Eunmi
    • Journal of Information Processing Systems
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    • v.16 no.2
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    • pp.377-393
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    • 2020
  • Freight management systems require a new business model for rapid decision making to improve their business processes by dynamically analyzing the previous experience data. Moreover, the amount of data generated by daily business activities to be analyzed for making better decisions is enormous. Online-to-offline or offline-to-online (O2O) is an electronic commerce (e-commerce) model used to combine the online and physical services. Data analysis is usually performed offline. In the present paper, to extend its benefits to online and to efficiently apply the big data analysis to the freight management system, we suggested a system architecture based on O2O services. We analyzed and extracted the useful knowledge from the real-time freight data for the period 2014-2017 aiming at further business development. The proposed system was deemed useful for truck management companies as it allowed dynamically obtaining the big data analysis results based on O2O services, which were used to optimize logistic freight, improve customer services, predict customer expectation, reduce costs and overhead by improving profit margins, and perform load balancing.

Use of big data analysis to investigate the relationship between natural radiation dose rates and cancer incidences in Republic of Korea

  • Joo, Han Young;Kim, Jae Wook;Moon, Joo Hyun
    • Nuclear Engineering and Technology
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    • v.52 no.8
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    • pp.1798-1806
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    • 2020
  • In this study, we investigated whether there is a significant relationship between the natural radiation dose rate and the cancer incidences in Korea by using a big data analysis. The natural dose rate data for this analysis were the measurement data obtained from the 171 monitoring posts of the 113 administrative districts in Korea over the 10 years from 2007 to 2016. The relative cancer incidences for this analysis were the difference in the cancer patients per hundred thousand people year-on-year in the administrative districts with the five highest and the five lowest natural gamma dose rates each year over the same period. To analyze the correlation between the two variables, Spearman's rank correlation coefficient between the two rates was derived using R, a well-known big data analysis tool. The analysis showed that Spearman's rank correlation coefficient was more than 0.05 and that the correlation between the two variables was not statistically significant.

A Case Study on Big Data Analysis Systems for Policy Proposals of Engineering Education (공학교육 정책제안을 위한 빅데이터 분석 시스템 사례 분석 연구)

  • Kim, JaeHee;Yoo, Mina
    • Journal of Engineering Education Research
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    • v.22 no.5
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    • pp.37-48
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    • 2019
  • The government has tried to develop a platform for systematically collecting and managing engineering education data for policy proposals. However, there have been few cases of big data analysis platform for policy proposals in engineering education, and it is difficult to determine the major function of the platform, the purpose of using big data, and the method of data collection. This study aims to collect the cases of big data analysis systems for the development of a big data system for educational policy proposals, and to conduct a study to analyze cases using the analysis frame of key elements to consider in developing a big data analysis platform. In order to analyze the case of big data system for engineering education policy proposals, 24 systems collecting and managing big data were selected. The analysis framework was developed based on literature reviews and the results of the case analysis were presented. The results of this study are expected to provide from macro-level such as what functions the platform should perform in developing a big data system and how to collect data, what analysis techniques should be adopted, and how to visualize the data analysis results.