효율적 데이터 마이닝을 위한 데이터 범주화에 관한 방법론

• 영문명: A Methodology on Classification of Data for Effective Data Mining
• 발행기관: 한국산업경영시스템학회
• 저자명: 임영문 곽준구
• 간행물 정보: 『한국산업경영시스템학회 학술대회』2004년 춘계학술대회 논문집, 295~298쪽, 전체 4쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2004.04.01

영문 초록

  In general, data mining has iterative processes with the following five steps: Data Selection, Cleansing, Transformation, Mining, Interpretation. Among these steps, steps of data selection and cleansing are performed to classify data. There are two types of data, continuous data and discrete data. Discrete data has a classified structure and it is easy to obtain rules from data. However, there are no general rules for classified method of data in continuous data. So, the result of data analysis will be differed from the classified method of data in continuous data. This research presents a methodology that can obtain the rules from data and classify data according to situations in DBMS (Data Base Management Systems).

목차

Abstract
1. 서론
2. 데이터의 종류 및 데이터 마이닝 기법
3. 결론 및 추후 연구
4. 감사의 글
참고 문헌