Association Rule Mining by Environmental Data Fusion

다국어 초록 (Multilingual Abstract)

Data fusion is the process of combining multiple data in order to produce information of tactical value to the user. 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. In this paper, we develop sas macro program for statistical matching which is one of five branch types for data fusion. And then we apply data fusion and association rule techniques to environmental data.

참고문헌 (Reference)

1 박희창, "의사결정나무 기법을 이용한 사회지표조사 자료 분석" 한국자료분석학회 7 (7): 773-783, 2005

2 김호종, "신경망 기반 추천 모델의 성능향상을 위한 정보의 융합" 2003 (2003): 422-424, 2003

3 최기주, "링크 통행시간 추정을 위한 데이터 퓨전 알고리즘의 개발" 16 (16): 177-195, 1998

4 박성원, "데이터 퓨전을 이용한 얼굴영상 인식 및 인증에 관한 연구" 11 (11): 302-306, 2001

5 손소영, "데이터 융합, 앙상블과 클러스터링을 이용한 교통사고 심각도 분류분석" 대한산업공학회 2000 : 597-600, 2000

6 신형원, "다구찌 디자인을 이용한 데이터 퓨전 및 군집분석 분류 성능 비교" 대한산업공학회 2000 : 601-604, 2000

7 Saygin Y., "Using Unknowns to Prevent Discovery of Association Rules" 2002

8 Toivonen H., "Sampling Large Database for Association Rules" 1996

9 National Statistics, "National Statistics Code of Practice Protocol on Data Matching"

10 Agrawal R., "Mining association rules between sets of items in large databases" 1993

11 Agrawal R., "Fast algorithms for mining association rules" 1994

12 Sergey B., "Dynamic itemset counting and implication rules for market data" 1997

13 Park J. S., "An effective hash-based algorithms for mining association rules" 1995

14 Cheung D. W., "A Fast distribution algorithm for mining association rules" 1996