Contiguous item sequential pattern mining using UpDown Tree

被引:7
|
作者
Chen, Jinlin [1 ]
机构
[1] CUNY Queens Coll, Dept Comp Sci, Flushing, NY 11367 USA
关键词
data mining algorithm; sequential pattern; contiguous sequential pattern; transaction database; sequence database; performance analysis;
D O I
10.3233/IDA-2008-12103
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper the problem of Contiguous Item Sequential Pattern ( CISP) Mining is presented as a sequential pattern mining problem under two constraints. First, each element in a sequence consists of only one item. Second, items appearing in the sequences that contain a pattern must be adjacent with respect to the underlying order as they appear in the pattern. Even though the problem of CISP mining can be solved by using previous approaches on sequential pattern mining under a general constraint description framework, this may lead to poor performance due to the large searching space. To efficiently solve this problem, a new data structure, UpDown Tree, is proposed for CISP mining. UpDown Tree based approach can greatly improve the efficiency of CISP mining in terms of both time and memory comparing to previous approaches. An extensive experimental study has shown promising results with our approach.
引用
收藏
页码:25 / 49
页数:25
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