Association rules are the discovery of previously unknown, potentially useful and hidden knowledge in databases. Many algorithms have been proposed to find association rules in databases. Due to the diverse use's interest and preference to items, former algorithms do not work well in real world application. That is to say, in most algorithms of mining association rules, the items are considered to have equal time weight and are not dealt with quantitative attributes. Hence, to improve former algorithms, we propose an algorithm in this paper to mine fuzzy association rules considering time weight of each item and quantity of each item.

Abstract
 1. 서론
  1.1 연구 배경
 2. 기존 연구 고찰
  2.1 연관규칙탐색
 3. 제안하는 알고리듬
  3.1 정보의 시간 가중치 계산
 4. 결론
 참고문헌

• 김준규(한양대학교 산업공학과)
• 안광일(한양대학교 산업공학과)
• 김성집(한양대학교 산업공학과)