• Title/Summary/Keyword: 빅데이터 분석학

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The Necessity and Case Analysis of Bigdata Quality Control in Medical Institution (의료기관 빅데이터 품질관리의 필요성과 사례 분석)

  • Choi, Hye Rin;Lee, Seung Won;Kim, YoungAh;Lee, Jong Ho;Koh, Hong;Kim, Hyeon Chang
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.67-74
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    • 2017
  • The use of Bigdata plays an important role in all areas of society. Especially in the health care field, the role of Bigdata is very considerable because it deals with people's life and health. However, the interest and awareness of quality control of medical data is markedly low. Because the low-quality medical Bigdata leads to national loss and public health impairment, quality control of medical Bigdata is needed. The purpose of this research is to present the direction of medical Bigdata quality management by examining literature and cases of domestic and foreign medical Bigdata quality management practices. In addition, as a case of medical Bigdata quality control in the Y medical institution in Korea, activities of a Bigdata quality management TFT and results of a survey conducted for major data users in the hospital were presented.

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The Types of Road Weather Big Data and the Strategy for Their Use: Case Analysis (도로 기상 빅데이터 유형별 활용 전략: 국내외 사례 분석)

  • Hahm, Yukun;Jun, YongJoo;Kim, KangHwa;Kim, Seunghyun
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.129-140
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    • 2017
  • Weather acts through low visibility, precipitation, high winds, and temperature extremes to affect driver capabilities, vehicle performance (i.e., traction, stability and maneuverability), pavement friction, roadway infrastructure, crash risk, traffic flow, and agency productivity. Recently a variety of road weather big data sources such as CCTV, road sensor/systems, car sensor have been developed to solve the weather-related problems, This study identifies and defines the types and characteristics of these sources to suggest how to utilize them for car safety and efficiency as well as road management through analyzing domestic and oversea cases of road weather big data applications.

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Implementing System for Dynamic Constructing and Clustering on KEGG Pathway Network (KEGG 패스웨이 네트워크 동적 구축 및 클러스터링 시스템 개발)

  • Seo, Dongmin;Lee, Min-Ho;Yu, Seok Jong
    • Proceedings of the Korea Contents Association Conference
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    • 2015.05a
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    • pp.231-232
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    • 2015
  • 최근 유전체학, NGS(Next Generation Sequencing) 기술, IT/NT 장비의 발전 등에 따라 방대한 양의 바이오-메디컬 데이터가 생산되고, 이에 따라 빅데이터를 활용한 헬스케어 산업이 급속히 발달하고 있으며, 이와 관련된 빅데이터 기술은 국민의 건강 증대와 건강한 고령 삶을 제공하는 핵심 기술로 급부상하고 있다. 패스웨이는 단백질, 유전자, 세포 등의 생체적 요소 간의 역학관계 혹은 상호작용 등을 네트워크 형식으로 표현한 생물학적 심층지식으로, 바이오-메디컬 빅데이터 분석에 있어서 널리 활용되고 있다. 하지만 패스웨이는 매우 다양한 형태를 갖고 용량이 매우 큰 빅데이터로 이를 분석하는데 많은 시간이 소요된다. 그래서 본 논문에서는 세계적으로 가장 우수하고 방대한 양의 패스웨이를 제공하는 KEGG 패스웨이 데이터베이스로부터 사용자가 관심 갖는 패스웨이만을 자동 수집하고 패스웨이 간 계층구조를 기반으로 네트워크를 구성 후, 해당 패스웨이 네트워크에 대한 클러스터링과 핵심 패스웨이 선정을 통해 패스웨이 간의 역학관계 또는 상호작용을 직관적으로 분석할 수 시스템을 제안했다.

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Sales Volume Prediction Model for Temperature Change using Big Data Analysis (빅데이터 분석을 이용한 기온 변화에 대한 판매량 예측 모델)

  • Back, Seung-Hoon;Oh, Ji-Yeon;Lee, Ji-Su;Hong, Jun-Ki;Hong, Sung-Chan
    • The Journal of Bigdata
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    • v.4 no.1
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    • pp.29-38
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    • 2019
  • In this paper, we propose a sales forecasting model that forecasts the sales volume of short sleeves and outerwear according to the temperature change by utilizing accumulated big data from the online shopping mall 'A' over the past five years to increase sales volume and efficient inventory management. The proposed model predicts sales of short sleeves and outerwear according to temperature changes in 2018 by analyzing sales volume of short sleeves and outerwear from 2014 to 2017. Using the proposed sales forecasting model, we compared the sales forecasts of 2018 with the actual sales volume and found that the error rates are ±1.5% and ±8% for short sleeve and outerwear respectively.

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Keyword Analysis of Data Technology Using Big Data Technique (빅데이터 기법을 활용한 Data Technology의 키워드 분석)

  • Park, Sung-Uk
    • Journal of Korea Technology Innovation Society
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    • v.22 no.2
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    • pp.265-281
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    • 2019
  • With the advent of the Internet-based economy, the dramatic changes in consumption patterns have been witnessed during the last decades. The seminal change has led by Data Technology, the integrated platform of mobile, online, offline and artificial intelligence, which remained unchallenged. In this paper, I use data analysis tool (TexTom) in order to articulate the definitfite notion of data technology from Internet sources. The data source is collected for last three years (November 2015 ~ November 2018) from Google and Naver. And I have derived several key keywords related to 'Data Technology'. As a result, it was found that the key keyword technologies of Big Data, O2O (Offline-to-Online), AI, IoT (Internet of things), and cloud computing are related to Data Technology. The results of this study can be used as useful information that can be referred to when the Data Technology age comes.

A Trip Mobility Analysis using Big Data (빅데이터 기반의 모빌리티 분석)

  • Cho, Bumchul;Kim, Juyoung;Kim, Dong-ho
    • The Journal of Bigdata
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    • v.5 no.2
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    • pp.85-95
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    • 2020
  • In this study, a mobility analysis method is suggested to estimate an O/D trip demand estimation using Mobile Phone Signaling Data. Using mobile data based on mobile base station location information, a trip chain database was established for each person and daily traffic patterns were analyzed. In addition, a new algorithm was developed to determine the traffic characteristics of their mobilities. To correct the ping pong handover problem of communication data itself, the methodology was developed and the criteria for stay time was set to distinguish pass by between stay within the influence area. The big-data based method is applied to analyze the mobility pattern in inter-regional trip and intra-regional trip in both of an urban area and a rural city. When comparing it with the results with traditional methods, it seems that the new methodology has a possibility to be applied to the national survey projects in the future.

Big Data-based Medical Clinical Results Analysis (빅데이터 기반 의료 임상 결과 분석)

  • Hwang, Seung-Yeon;Park, Ji-Hun;Youn, Ha-Young;Kwak, Kwang-Jin;Park, Jeong-Min;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.187-195
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    • 2019
  • Recently, it has become possible to collect, store, process, and analyze data generated in various fields by the development of the technology related to the big data. These big data technologies are used for clinical results analysis and the optimization of clinical trial design will reduce the costs associated with health care. Therefore, in this paper, we are going to analyze clinical results and present guidelines that can reduce the period and cost of clinical trials. First, we use Sqoop to collect clinical results data from relational databases and store in HDFS, and use Hive, a processing tool based on Hadoop, to process data. Finally we use R, a big data analysis tool that is widely used in various fields such as public sector or business, to analyze associations.

A Study on the Selection of Core Services for Geo-Spatial Big Data (공간 빅데이터 핵심서비스 선정에 관한 연구)

  • Lee, Myeong Ho;Park, Joon Min;Shin, Dong bin;Ahn, Jong Wook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.5
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    • pp.385-396
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    • 2015
  • The purpose of this study are in selecting a core service and drawing an analysis functions and service sector, based on contents of geo-spatial big data. For the study, the demand survey in the methodology has to be done by reviewing of preceding geo-spatial big data service. The survey has conducted by targeting on those experts in Industry-Academy-Research cooperation. From the survey, we could draw out requirements for the analysis function and the geo-spatial big data service sector. Also, order of priorities in service of four fields(Society, Environment, Economy, Humanities) has been utilized by a QFD(Quality Function Deployment). With the data, the first two priorities and required sectors for each field were selected for the analysis functions. From the result, we could suggest the core service model(plan), and also expect developments following each sectoral core service in the future.

A Study On The Difference By Health Literacy Level Of Chronic Patients Analyzed By Medical Big Data (의료 빅데이터로 분석한 만성질환자의 건강정보 수준별 차이 연구)

  • Park Saehan;Lee Sangyeop;Han Giheon;Kim Jiyeon;Koo Jeehyun;Jung Byoungho
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.4
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    • pp.73-86
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    • 2023
  • The purpose of this study is to prepare basic data that can be applied to the development of personalized programs in which chronic patients can actively participate in health care on their own, by analyzing the relationship between health literacy, level of metal health, and level of life health of patients with chronic diseases. For the study, the Korean Medical Panel's annual data(Version 2.1) was used, and 4,095 people aged 19 or older with chronic diseases and without disabilities were extracted, and frequency analysis, t-test, ANOVA, and chi-squared goodness of fit test, etc. were performed with IBM SPSS Statistics 26.0. As a result, it was found that the higher health literacy, the higher level of mental health and level of life health. In addition, the distribution between health literacy, level of mental health, and level of life health was found to be different from each other. Respondents with higher ability to health literacy tend to evaluate level of metal health and life health lower, and the rate of change in this trend was relatively higher than the rate of change in the tendency to evaluate level of mental health and life health higher in respondents with lower ability to health literacy.

Trends of South Korea's Informatization and Libraries' Role Based on Newspaper Big Data (신문 빅데이터를 바탕으로 본 국내 정보화의 경향과 도서관의 역할)

  • Na, Kyoungsik;Lee, Jisu
    • The Journal of the Korea Contents Association
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    • v.18 no.9
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    • pp.14-33
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    • 2018
  • The purpose of this study to analyze the informatization trends in Korea through objective newspaper data for the period from 1998 to 2017 for informatization and library in four newspapers including KyoungHyang Newspaper, Kookmin Ilbo, Hankyoreh and Hankookilbo. Based on the analysis results of metadata and related words using BIGKinds, a news big data system, this study presented analysis of simple frequency, classification and classification of the keywords 'information', 'informatization' and 'library'. Based on the results, we compared and analyzed the tendency of informatization in the media through comparison with the 'Information White Paper' which is the publication of government agencies and with research about the research topic of 4 academic journals in the Library and Information Science field. This study tried to interpret the trends of informatization based on the media and it is meaningful that we analyzed the big data of newspaper article which is the long term and time series data. Based on the results of the study, implications of the growth and development of libraries with domestic informatization were suggested. It is expected that we will be able to create a basic framework for developing library informatization policy through the further studies.