• 한국데이터정보과학회:학술대회논문집
• /
• 2003.05a
• /
• pp.159-170
• /
• 2003

This Paper analyzed simultaneous activities of the time use survey by Korea National Statistical Office to use data mining‘s association rule. The survey of National Statistical Office in 1999 considered general analysis for simultaneous activities. But if we use the association rule, we can found the ratio of particular activities at the same time. And we found the probability that another activities practise if we act one particular activity. Using this association rule of data mining we can do more developed and analytical sociological study.

• Proceedings of the PSK Conference
• /
• 2003.10b
• /
• pp.68.2-68.2
• /
• 2003

We performed this survey to hear Yeungnam University Graduates' opinion on the current curriculum for the purpose of creating an education system of “practically competent person” instead of simply “competent person”. Questionnaire was made up of 13 multiple-choice questions and 1 descriptive question by Curriculum Reform Task Force of Yeungnam University. The survey was administered to randomly chosen 50 graduates by e-mail on August 1, 2003 and was collected between August 1 and August 10, 2003 for the analysis of respondent’s reply. (omitted)

• Economic and Environmental Geology
• /
• v.33 no.1
• /
• pp.41-50
• /
• 2000

Geo-radar survey which has the advantage of high-resolution and relatively fast survey has been widely used for engineering and environmental problems. Three-dimensional effects have to be considered in the interpretation of geo-radar for high-resolution. However, there exists a trouble on the analysis of the three dimensional effects. To solve this problem an efficient three dimension numerical modeling algorithm is needed. Numerical radar modeling in three dimensional case requires large memory and long calculating time. In this paper, a finite difference method time domain solution to Maxwell's equations for simulating electromagnetic wave propagation in three dimensional media was developed to make economic algorithm which requires smaller memory and shorter calculating time. And in using boundary condition Liao absorption boundary. The numerical result of cross-hole radar survey for tunnel is compared with real data. The two results are well matched. To prove application to three dimensional analysis, the results with variation of tunnel's incident angle to survey cross-section and the result when the tunnel is parallel to the cross-section were examined. This algorithm is useful in various geo-radar survey and can give basic data to develop dat processing and inversion program.

• Journal of the Korean Data and Information Science Society
• /
• v.17 no.4
• /
• pp.1201-1208
• /
• 2006

Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.4
• /
• pp.927-935
• /
• 2007

Currently, Gyeongnam province is executing the social index survey every year to the provincials. But, this survey has the limit of the analysis as execution of the different survey per 3 year cycles. The solution of this problem is data fusion. Data fusion is the process of combining multiple data in order to provide information of tactical value to the user. But, data fusion doesn#t mean the ultimate result. Therefore, efficient analysis for the data fusion is also important. In this study, we present data fusion method of statistical survey data. Also, we suggest application methodology of association rule mining by clustering through data fusion of statistical survey data.

• 한국데이터정보과학회:학술대회논문집
• /
• 2006.11a
• /
• pp.21-27
• /
• 2006

Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.25 no.5
• /
• pp.46-52
• /
• 2002

Today's database system needs to collect huge amount of questionnaire that results from development of the information technology by the internet, so it has to be administrable. However, there are many difficulties concerned with finding analytic data or useful information in the high capacity-database. Data mining can solve these problems and utilize the database. Questionnaire analysis that uses data mining has drawn relevant patterns that did not look or was tended to overlook before. These patterns can be applied by a new business rule. The purpose of this research is to analyze the questionnaire results and to present the result that can help to make decision easily with data mining. Recognition and analysis about these techniques of data mining show suitable type of questionnaire survey. This research focus on the form of present composition and the model of suitable questionnaire to analyze the type of it. Also, the comparison between the actual questionnaire result and the conventional statistical analysis is examined.

• Journal of the Korea Safety Management & Science
• /
• v.14 no.2
• /
• pp.237-243
• /
• 2012

The more the satisfied customers increases in customer satisfaction survey, the more the company has difficultly in improving the customer satisfaction. In addition, the effectiveness of practical application of customer satisfaction survey decreases due to its constitution limitation on its data analysis. To overcome these problems, it is necessary to develop a new method to identify the strategy meanings and find the dissatisfied factors of satisfied customers using the satisfied customers reclassification. This study focuses on the satisfied customer segmentation using Latent Class Analysis. The case study shows that the satisfied customers are divided into three subgroups using Latent Class Analysis and we draw meaning results such as satisfaction and dissatisfaction factors through analyzing each group. This study is expected to play the role as the groundwork for the revitalization of customer satisfaction survey.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.5
• /
• pp.983-992
• /
• 2012

Social indicator survey can identify the state of society as a whole. When we create a policy, social indicator survey can reflect the public opinion of the region. Social indicator survey is an important measure of social change. Social indicator survey has been conducted in many municipalities (Seoul, Incheon, Busan, Ulsan, Gyeongsangnamdo, etc.). But, the result of social indicator survey analysis is mainly the basic statistical analysis. In this study, we propose a new data mining methodology for effective analysis. We propose a 3-step complex data mining in society indicator survey. 3-step complex data mining uses three data mining method (intervening association rule, clustering, decision tree).

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.6
• /
• pp.487-492
• /
• 2022

Universities are looking for various methods to enhance educational competence level suitable for the rapidly changing social environment. This study suggests a method to promote academic and educational achievements by reducing drop-out rate from their majors through implementation of pre-survey of satisfaction that revised and complemented survey items. To supplement the CQI method implemented after a general satisfaction survey, a pre-survey of satisfaction was carried out. To consolidate students' competences, this study made prediction and analysis of data with more importance possible using the Random Forest of the machine learning technique that can be applied to AI Medici platform, whose design is underway. By pre-processing the pre-survey of satisfaction, the students information enrolled in classes were defined as an explanatory variable, and they were classified, and a model was created and learning was conducted. For the experimental environment, the algorithms and sklearn library related in Jupyter notebook 3.7.7, Python 3.7 were used together. This study carried out a comparative analysis of change in educational satisfaction survey, carried out after classes, and trends in the drop-out students by reflecting the results of the suggested method in the classes.