원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
vol.2 no.3
2009.09
pp.1-12
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
In this paper, we present a new algorithm for mining generalized association rules. We develop the algorithm which scans database one time only and use Tidset to compute the support of generalized itemset faster. A tree structure called GIT-tree, an extension of IT-tree, is developed to store database for mining frequent itemsets from hierarchical database. Our algorithm is often faster than MMS_Cumulate, an algorithm mining frequent itemsets in hierarchical database with multiple minimum supports, in experimental databases.
목차
Abstract
1. Introduction
2. Concepts
2.1. Definition 1
2.2. Definition 2
2.3. Definition 3
2.4. Definition 4
2.5. Definition 5
3. GIT-tree
3.1. Vertex
3.2. Arc
4. Algorithm for mining frequent itemsets in hierarchical database basedon GIT-tree
4.1. Algorithm
4.2. Illustration
4.3. Diffset for fast computing the support
5. Experimental results
6. Conclusion and future works
References
1. Introduction
2. Concepts
2.1. Definition 1
2.2. Definition 2
2.3. Definition 3
2.4. Definition 4
2.5. Definition 5
3. GIT-tree
3.1. Vertex
3.2. Arc
4. Algorithm for mining frequent itemsets in hierarchical database basedon GIT-tree
4.1. Algorithm
4.2. Illustration
4.3. Diffset for fast computing the support
5. Experimental results
6. Conclusion and future works
References
저자정보
참고문헌
자료제공 : 네이버학술정보