상대지지도를 이용한 효율적인 연관규칙 탐사 알고리즘 = An Efficient Algorithm for Mining Association Rules using a Relative Support

다국어 초록 (Multilingual Abstract)

Data mining is used to discover patterns and relationships in data, with an emphasis on large observational data bases. Association rule mining is an important model in data mining. Its mining algorithms discover all item association rules in the data that satisfy the user-specified minimum support(minsup) and minimum confidence(miniconf) constraints. The paper proposes an efficient algorithm to find association rules in large databases. The proposed algorithm is to discover multiple-level data items using a relative support. which are concurrency data items with high ratio even though they have a few frequencies. A relative support is measures using relative frequencies in data items.

목차 (Table of Contents)

• I.서론
• II.연관 규칙과 관련 연구
• 1.연관 규칙
• 2.관련연구
• III.상대 지지도를 이용한 다단계 연관 규칙 탐사
• 1.상대 지지도
• 2.minsup과 Rsup에 의한 후보 항목 집합의 구성
• 3.알고리즘
• IV.결론