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Association Rule of Gyeongnam Social Indicator Survey Data for Environmental Information
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  • Association Rule of Gyeongnam Social Indicator Survey Data for Environmental Information
  • Association Rule of Gyeongnam Social Indicator Survey Data for Environmental Information
저자명
Park. Hee-Chang,Cho. Kwang-Hyun
간행물명
한국데이터정보과학회지
권/호정보
2005년|16권 1호|pp.59-69 (11 pages)
발행정보
한국데이터정보과학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Data mining is the method to find useful information for large amounts of data in database It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. We analyze Gyeongnam social indicator survey data by 2001 using association rule technique for environment information. Association rule mining searches for interesting relationships among items in a given large data set. 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. We can use to environmental preservation and environmental improvement by association rule outputs