• Title/Summary/Keyword: Data analysis study

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Study of Mental Disorder Schizophrenia, based on Big Data

  • Hye-Sun Lee
    • International Journal of Advanced Culture Technology
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    • v.11 no.4
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    • pp.279-285
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    • 2023
  • This study provides academic implications by considering trends of domestic research regarding therapy for Mental disorder schizophrenia and psychosocial. For the analysis of this study, text mining with the use of R program and social network analysis method have been used and 65 papers have been collected The result of this study is as follows. First, collected data were visualized through analysis of keywords by using word cloud method. Second, keywords such as intervention, schizophrenia, research, patients, program, effect, society, mind, ability, function were recorded with highest frequency resulted from keyword frequency analysis. Third, LDA (latent Dirichlet allocation) topic modeling result showed that classified into 3 keywords: patient, subjects, intervention of psychosocial, efficacy of interventions. Fourth, the social network analysis results derived connectivity, closeness centrality, betweennes centrality. In conclusion, this study presents significant results as it provided basic rehabilitation data for schizophrenia and psychosocial therapy through new research methods by analyzing with big data method by proposing the results through visualization from seeking research trends of schizophrenia and psychosocial therapy through text mining and social network analysis.

A Study on Patent Data Analysis and Competitive Advantage Strategy using TF-IDF and Network Analysis (TF-IDF와 네트워크분석을 이용한 특허 데이터 분석과 경쟁우위 전략수립에 관한 연구)

  • Yun, Seok-Yong;Han, Kyeong-Seok
    • Journal of Digital Contents Society
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    • v.19 no.3
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    • pp.529-535
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    • 2018
  • Data is explosively growing, but many companies are still using data analysis only for descriptive analysis or diagnostic analysis, and not appropriately for predictive analysis or enterprise technology strategy analysis. In this study, we analyze the structured & unstructured patent data such as IPC code, inventor, filing date and so on by using big data analysis techniques such as network analysis and TF-IDF. Through this analysis, we propose analysis process to understand the core technology and technology distribution of competitors and prove it through data analysis.

Analysis on Types of Golf Tourism After COVID-19 by using Big Data

  • Hyun Seok Kim;Munyeong Yun;Gi-Hwan Ryu
    • International Journal of Advanced Culture Technology
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    • v.12 no.1
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    • pp.270-275
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    • 2024
  • Introduction. In this study, purpose is to analize the types of golf tourism, inbound or outbound, by using big data and see how movement of industry is being changed and what changes have been made during and after Covid-19 in golf industry. Method Using Textom, a big data analysis tool, "golf tourism" and "Covid-19" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 1 st January, 2023 to 31st December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "golf tourism" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, top 36 keywords with the highest relevance and search frequency were selected and applied to this study. The top 36 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. Results By using big data analysis, it was found out option of oversea golf tourism is affecting on inbound golf travel. "Golf", "Tourism", "Vietnam", "Thailand" showed high frequencies, which proves that oversea golf tour is now the re-coming trends.

A Comparison of Starbucks between South Korea and U.S.A. through Big Data Analysis (빅데이터 분석을 통한 한국과 미국의 스타벅스 비교 분석)

  • Jo, Ara;Kim, Hak-Seon
    • Culinary science and hospitality research
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    • v.23 no.8
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    • pp.195-205
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    • 2017
  • The purpose of this study was to compare the Starbucks in South Korea with Starbucks in U.S.A through the semantic network analysis of big data by collecting online data with SCTM(Smart Crawling & Text Mining) program which was developed by big data research institute at Kyungsung University, a data collecting and processing program. The data collection period was from January 1st 2014 to December 7th 2017, and packaged Netdraw along with UCINET 6.0 were utilized for data analysis and visualization. After performing CONCOR(convergence of iterated correlation) analysis and centrality analysis, this study illustrated the current characteristics of Starbucks for Korea and U.S.A reflected by the social network and the differences between Korea and U.S.A. Since the Starbucks was greatly developed, especially in Korea. this study also was supposed to provide significant and social-network oriented suggestions for Starbucks USA, Starbucks Korea and also the whole coffee industry. Also this study revealed that big data analytics can generate new insights into variables that have been extensively studied in existing hospitality literature. In addition, implications for theory and practice as well as directions for future research are discussed.

Research Trend Analysis for Sustainable QR code use - Focus on Big Data Analysis

  • Lee, Eunji;Jang, Jikyung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3221-3242
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    • 2021
  • The purpose of the study is to examine the current study trend of 'QR code' and suggest a direction for the future study of big data analysis: (1) Background: study trend of 'QR code' and analysis of the text by subject field and year; (2) Methodology: data scraping and collection, EXCEL summary, and preprocess and big data analysis by R x 64 4.0.2 program package; (3) the findings: first, the trend showed a continuous increase in 'QR code' studies in general and the findings were applied in various fields. Second, the analysis of frequent keywords showed somewhat different results by subject field and year, but the overall results were similar. Third, the visualization of the frequent keywords also showed similar results as that of frequent keyword analysis; and (4) the conclusions: in general, 'QR code' studies are used in various fields, and the trend is likely to increase in the future as well. And the findings of this study are a reflection that 'QR code' is an aspect of our social and cultural phenomena, so that it is necessary to think that 'QR code' is a tool and an application of information. An expansion of the scope of the analysis is expected to show us more meaningful indications on 'QR code' study trends and development potential.

A Method for Engineering Change Analysis by Using OLAP (OLAP를 이용한 설계변경 분석 방법에 관한 연구)

  • Do, Namchul
    • Korean Journal of Computational Design and Engineering
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    • v.19 no.2
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    • pp.103-110
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    • 2014
  • Engineering changes are indispensable engineering and management activities for manufactures to develop competitive products and to maintain consistency of its product data. Analysis of engineering changes provides a core functionality to support decision makings for engineering change management. This study aims to develop a method for analysis of engineering changes based on On-Line Analytical Processing (OLAP), a proven database analysis technology that has been applied to various business areas. This approach automates data processing for engineering change analysis from product databases that follow an international standard for product data management (PDM), and enables analysts to analyze various aspects of engineering changes with its OLAP operations. The study consists of modeling a standard PDM database and a multidimensional data model for engineering change analysis, implementing the standard and multidimensional models with PDM and data cube systems and applying the implemented data cube to core functions of engineering change management, the evaluation and propagation of engineering changes.

A Study on Error of Frequence Rainfall Estimates Using Random Variate (무작위변량을 이용한 강우빈도분석시 내외삽오차에 관한 연구)

  • Chai, Han Kyu;Eam, Ki Ok
    • Journal of Industrial Technology
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    • v.20 no.A
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    • pp.159-167
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    • 2000
  • In the study rainfall frequency analysis attemped the many specific property data record duration it is differance from occur to error-term and probability ditribution of concern manifest. error-term analysis of method are fact sample data using method in other hand it is not appear to be fault that sample data of number to be small random variates. Therefore, day-rainfall data: to randomicity consider of this study sample data to the Monte Carlo method by randomize after data recode duration of form was choice method which compared an assumed maternal distribution from splitting frequency analysis consequence. In the conclusion, frequency analysis of chuncheon region rainfall appeared samll RMSE to the Gamma II distribution. In the rainfall frequency analysis estimate RMSE using random variates great transform, RMSE is appear that return period increasing little by little RMSE incresed and data number incresing to RMSE decreseing.

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A Study on the Analysis and Application of the Satellite Data for Study of Urban and Region (도시 및 지역연구를 위한 인공위성 Data의 분석 및 그 활용방안에 관한 연구)

  • 안철호;윤정섭;안기원
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.3 no.1
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    • pp.1-13
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    • 1985
  • This study is about the analysis and application of the Satellite(in particular, LANDSAT) Data for the study of urban and region. Land cover maps and change of each classes for a period of years of Seoul, Daejeon, and Incheon cities were extracted by use of LANDSAT MSS Data and MSS Image Analysis System. From the results of this study, it was proved that Satellite data could be used on the study of urban and region to obtain fully fruitful results.

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Component Development and Importance Weight Analysis of Data Governance (Data Governance 구성요소 개발과 중요도 분석)

  • Jang, Kyoung-Ae;Kim, Woo-Je
    • Journal of the Korean Operations Research and Management Science Society
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    • v.41 no.3
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    • pp.45-58
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    • 2016
  • Data are important in an organization because they are used in making decisions and obtaining insights. Furthermore, given the increasing importance of data in modern society, data governance should be requested to increase an organization's competitive power. However, data governance concepts have caused confusion because of the myriad of guidelines proposed by related institutions and researchers. In this study, we re-established the concept of ambiguous data governance and derived the top-level components by analyzing previous research. This study identified the components of data governance and quantitatively analyzed the relation between these components by using DEMATEL and context analysis techniques that are often used to solve complex problems. Three higher components (data compliance management, data quality management, and data organization management) and 13 lower components are derived as data governance components. Furthermore, importance analysis shows that data quality management, data compliance management, and data organization management are the top components of data governance in order of priority. This study can be used as a basis for presenting standards or establishing concepts of data governance.

A Study on the Principal Component Analysis of Anthropometric Data (인체계측치(人體計測値)의 주성분분석(主成分分析)에 관한 연구(硏究))

  • Lee, Sang-Do;Jeong, Jung-Hui;Kim, Geuk-Bae
    • Journal of the Ergonomics Society of Korea
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    • v.2 no.1
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    • pp.3-11
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    • 1983
  • Anthropometric data is most basic materials in the all studies related with it. Therefore, in anthropometric data, not only consideration of the state of variance, but more various analysis is needed. This study selected the 13 parts that properly show a whole characteristics of human body and, anthropometric data were obtained through the actual measurements for male and female workers who were engaged in production factory. And, to interpret anthropometric data, principal component analysis of multivariate analysis methods was applied.

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