基于分区的过渡模式快速挖掘方法

R. Subramanyam, S. Suvvari
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引用次数: 2

摘要

研究频率随时间变化的模式的动态行为是最近的兴趣。这种模式被称为过渡模式[1],只有在挖掘事务数据库中的频繁模式时才能发现。本文提出了一种基于分块的算法来寻找过渡模式的变化。我们的方法不需要在数据库中挖掘一组频繁的模式来启动查找过渡模式的过程,从而减少了对数据库的扫描次数。在[1]中,Tξ的取值范围是固定的,而我们用支持度来表示,因为它随着数据库的大小和最小模式支持值而变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Partition-Based Approach for Fast Mining of Transitional Patterns
Studying the dynamic behaviour of patterns whose frequency changes over time is of recent interest. Such patterns are named as transitional patterns [1] and were found only upon mining the frequent patterns in a transaction database. In this paper, a partition-based algorithm is proposed to find a variation of transitional patterns. Our approach do not require a set of frequent patterns mined over the database to initiate the process of finding transitional patterns and thus reduces the number of scans over the database. In [1] the range of Tξ was fixed, whereas we expressed it in terms of support so as it varies with the sizes of the databases and minimum pattern support value.
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