uCFS2: An Enhanced System that Mines Uncertain Data for Constrained Frequent Sets

被引:5
|
作者
Leung, Carson Kai-Sang [1 ]
Brajczuk, Dale A. [1 ]
机构
[1] Univ Manitoba, Winnipeg, MB, Canada
来源
PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL DATABASE ENGINEERING & APPLICATIONS SYMPOSIUM (IDEAS '10) | 2010年
基金
加拿大自然科学与工程研究理事会;
关键词
Data mining; frequent patterns; probabilistic databases; uncertain data; user constraints; TREE;
D O I
10.1145/1866480.1866486
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Frequent set mining searches for sets of items that are frequently co-occurring together. Existing algorithms mainly find all the frequent sets from precise data. However, there are real-life situations in which users are interested in only some tiny portions of the entire collection of frequent sets and/or the data to be mined are uncertain. Recently, a tree-based system was proposed to mine uncertain data for frequent sets that satisfy user-specified succinct constraints. However, non-succinct constraints exist. In this paper, we extend such a system to mine uncertain data for frequent sets that satisfy succinct as well as non-succinct constraints by effectively exploiting properties of these constraints.
引用
收藏
页码:32 / 37
页数:6
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