• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1077-1083
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• 2006

Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. In this paper we present association rule mining based antecedent variables. We call these rules to antecedent association rules. An antecedent variable is a variable that occurs before the independent variable and the dependent variable.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 추계학술대회
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• pp.197-213
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• 2003

One of the well-studied problems in data mining is the search for association rules. The goal of association rule mining is to find all the rules with support and confidence exceeding some user specified thresholds. In this paper we consider the relation between the measure of association and the criteria of association rule for ordinal data.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.707-718
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• 2003

The Korean Anthropometric Survey (Size Korea) is a sample survey which estimates on percentiles of several dimensional measurements of the human body and its component parts. The purpose of this study is to design a sample, which is designed on the base of 1997 survey database. Two different methods are considered to get the sample size for estimating the 5th and 95th percentile of body dimensions of Korean age range 0-80 years.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1007-1018
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• 2008

The purpose of this case study is to demonstrate database-marketing management. First, we explore original variables for insurance customer's data, modify them if necessary, and go through variable selection process before analysis. Then, we develop churn prediction models using logistic regression, neural network and SVM analysis. We also compare these three data mining models in terms of misclassification rate.

• 천문학논총
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• 제21권1호
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• pp.1-9
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• 2006

An archiving system designed to enable documenting database of astronomical images, with functions of search and download, is being developed by Korean Astronomical Data Center(KADC) of Korea Astronomy and Space Science Institute(KASI). The system consists of three PCs for web server, database server, and system management server. The search program for the web environment is operated in the web server. In the management server, several utility program we developed are installed: input program for the database, program for transfer from fits to jpg files, program for data recovery and management, and programs for statistics and connect management. The collected data would be sorted out by the system manager to input into the database. The online input is possible in an observatory where the data is produced. We applied the content management system(CMS) module for the database management. On the basic of CMS module, we set up a management system for the whole life cycle of metadata from creation and collection to storage and deletion of the data. For the search function, we employed a technique to extract indices from the metadata. In addition, MySQL is adopted for DBMS. We currently display about 2,700 and 25,000 photographs for astronomical phenomena and astronomical objects on the data, respectively.

• 디지털콘텐츠학회 논문지
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• 제8권2호
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• pp.149-156
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• 2007

본 논문에서는 통계 어플리케이션을 웹 서버에서 내려받기 하여 클라이언트에 저장, 설치하고 stand alone 형태로 운영되도록 개발된 DAVIS에 대하여 개발 기법과 구현된 형태를 연구하고, 서버 기반의 통계 프로그램과 클라이언트 기반의 통계 프로그램에 대하여 고찰한다. 그리고 이들 유형에 대한 장단점을 파악하여 좀 더 발전된 통계학습시스템의 설계 방안을 제안한다. 이 시스템은 클라이언트 요청에 의하여 클라이언트에서 어플리케이션이 실행되고, 통계 데이터는 데이터베이스 서버에서 로드하거나 사용자에 의해 클라이언트에서 입력하는 형태로 설계되어 통계 분석을 수행토록 한다.

• 농촌계획
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• 제11권2호
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• pp.43-49
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• 2005

As information has been brought to public attention, information storage as well as information usability has been important. Rural information is produced in many areas and institutions. However, it is difficult to use rural information comprehensively. Since formats for management are various, it is difficult to have unified frame. In this research, a schema of database fer integrating rural data is designed to improve usability using dimensional modeling. First of all, rural data are analyzed for designing integrated rural database schema. Rural data used are 'National Agricultural Statistics' and 'Gun annual statistical report'. Analysis shows that there are three considerations; administrative district, time-dependency and classification of data. Considering these three requisite, we designed database schema using dimensional modeling. The reason of using dimensional modeling is to improve usability and effectiveness. If the database was designed using ER modeling, many tables have to be joined every searching time. Separately from integrated rural database schema, user's database schema is designed considering usability. Through user's database, users can modify data or generate new data and save these processes. These make it possible to use generated data repeatedly. We evaluate usability, contribution, and effectiveness of data manipulation on the integrated rural database. We propose an integrated rural database structure improving the accessibility and usability of rural data and information and verified the data model based on a practical example.

• 한국산업보건학회지
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• 제33권1호
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• pp.78-90
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• 2023

Objectives: The purpose of this study is to standardize the process code of the work environment measurement database (WEMD) for the construction of a job-exposure matrix (JEM). Methods: The standard process code (SPC) was reclassified based on process similarity and drawing upon the code used in the existing K2B. It was supplemented through review by industrial hygiene experts. In addition, an index word database related to SPC was created and used for SPC search. A pilot evaluation project was conducted by experts to evaluate the validity of the newly reclassified standard process code. Results: A total of 70 final SPCs were developed, including 31 processes related to the construction industry. Using the Shiny program, we developed a standard code finder that can be used on the web (https://kscf.shinyapps.io/scf_app/). As a result of the pilot evaluation, it was determined that it was easier to search for standard codes than previous codes, so it was highly utilized. Conclusions: It is expected that JEM construction using industry-process information drawing on WEMD data will be possible using the 70 newly standardized process codes.

• 한국콘텐츠학회논문지
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• 제4권3호
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• pp.1-11
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• 2004

본 연구는 관광통계 프로세스 설계 지원 도구 개발을 통하여 업무 프로세스를 설계하고, 시스템을 구축함으로써, 관광통계를 체계적이고, 통합적으로 관리할 수 있도록 하고 관광개발계획 의사결정 지원도구로 활용하는데 목적이 있다. 이러한 목표하에 정보공급자, 정보생산자, 정보활용자의 3가지 요소로 이루어진 관광통계 프로세스 설계 지원 도구를 개발하였다. 이러한 프로세스 설계 지원 도구는 기존의 개발계획지표가 관광 관련 정책결정 및 개발계획수립에 효율적의 활용될 수 있도록 업무프로세스를 개선하고 시스템 구조를 합리화시킬 수 있다. 프로세스 설계 지원 도구를 활용하여,49개의 업무 프로세스를 설계하였고, 외부 기관과 연계되는 합리적인 데이터베이스를 설계하여, 관광통계정보시스템을 구축하였다. 그 결과 관광개발계획 수립시, 보다 합리적인 의사결정을 지원할 수 있게 되었다.

• Asian Journal of Business Environment
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• 제13권2호
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• pp.9-20
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• 2023

Purpose: This study aims to map the spatial distribution of poverty using nighttime light satellite images as a proxy indicator of economic activities and infrastructure distribution in D.I Yogyakarta, Indonesia. Research design, data, and methodology: This study uses official poverty statistics (National Socio-economic Survey (SUSENAS) and Poverty Database 2015) to compare satellite imagery's ability to identify poor urban areas in D.I Yogyakarta. National Socioeconomic Survey (SUSENAS), as poverty statistics at the macro level, uses expenditure to determine the poor in a region. Poverty Database 2015 (BDT 2015), as poverty statistics at the micro-level, uses asset ownership to determine the poor population in an area. Pearson correlation is used to identify the correlation among variables and construct a Support Vector Regression (SVR) model to estimate the poverty level at a granular level of 1 km x 1 km. Results: It is found that macro poverty level and moderate annual nighttime light intensity have a Pearson correlation of 74 percent. It is more significant than micro poverty, with the Pearson correlation being 49 percent in 2015. The SVR prediction model can achieve the root mean squared error (RMSE) of up to 8.48 percent on SUSENAS 2020 poverty data.Conclusion: Nighttime light satellite imagery data has potential benefits as alternative data to support regional poverty mapping, especially in urban areas. Using satellite imagery data is better at predicting regional poverty based on expenditure than asset ownership at the micro-level. Light intensity at night can better describe the use of electricity consumption for economic activities at night, which is captured in spending on electricity financing compared to asset ownership.