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  4. Mining Closed Multi-Dimensional Interval Patterns
 
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Mining Closed Multi-Dimensional Interval Patterns

Other Title
探勘封閉性多維度區間樣式
Journal
資訊管理學報
Journal Volume
19
Journal Issue
1
Pages
161 - 184
Date Issued
2012-01
Author(s)
ANTHONY J. T. LEE  
Fu-Chen Yang
Wei-Cheng Lee
DOI
10.6382/JIM.201201.0161
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/415140
Abstract
Many methods have been proposed to find frequent one-dimensional (1-D) interval patterns, where each event in the database is realized by a 1-D interval. However, the events in many applications are in nature realized by multi-dimensional intervals. Therefore, in this paper, we propose an efficient algorithm, called MIAMI, to mine closed multi-dimensional interval patterns from a database. The MIAMI algorithm employs a pattern tree to enumerate all closed patterns in a depth-first search manner. In the mining process, we devisethree effective pruning strategies to remove impossible candidates and perform a closure checking scheme to eliminate non-closed patterns. The experimental results show that the MIAMI algorithm is more efficient and scalable than the modified Apriori algorithm.
Type
journal article

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