In this paper, we present a temporal association rules based on item time intervals. A temporal association rules is an association rule that holds specific time intervals. If we consider itemset in the frequently purchased period, we can discovery more significant itemset satisfying minimum support. Because the previous study did not consider the time interval between purchased item, it could find itemset that did not satisfy the minimum support in case some item was frequently purchased in a specific period and rarely or not purchased in other period. Our approach use interval support which is counted by period with support and confidence in the association rule to discovery large itemset.

Abstract
 1. 서 론
  1.1 연구 배경
  1.2 연구 목적
 2. 기존연구 고찰
  2.1 Apriori 연관규칙을 이용한 연관규칙[4]
  2.2 Temporal 연관규칙[3]
 3. 제안하는 알고리즘
  3.1 용어 정리
  3.2 temporal 연관규칙 발견
  3.3 기존 연구와의 비교
 4. 항목의 시간 간격을 고려한 Temporal 연관 규칙 예제
  4.1 최소간격지지도 적용
  4.2 빈발항목 생성
 5. 결 론
 참고문헌

• 이경원(한양대학교 산업공학과)
• 김재련(한양대학교 산업공학과)