An Algorithm for Mining Conditional Hybrid Dimensional Association Rules using Boolean Matrix

被引：2
|
作者：
Khare, Neelu [1 ]
Adlakha, Neeru [2 ]
Pardasani, K. R. [3 ]
机构：
[1] Maulana Azad Natl Inst Technol, Dept Comp Applicat, Bhopal, MP, India
[2] SVNIT, Dept Appl Math, Surat, India
[3] Maulana Azad Natl Inst Technol, Dept Math, Bhopal, MP, India
来源：
2010 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2010), VOL 2 | 2010年
关键词：
Boolean matrix; hybrid dimensional association rule; relational calculus; multidimensional transaction database;
D O I：
10.1109/ICCAE.2010.5451707
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we present an algorithm of mining hybrid dimension association rules which satisfies the definite condition on the basis of multidimensional transaction database. Boolean Matrix based approach has been employed to generate frequent itemsets in multidimensional transaction databases. It adopts Boolean relational calculus to discover frequent predicate sets. When using this algorithm first time, it scans the database once and will generate the association rules. Apriori property is used in algorithm to prune the item sets. It is not necessary to scan the database again; it uses Boolean logical operations to generate the association rules. We illustrate the implementation of algorithm with the help of a simple example.
引用
收藏
页码：644 / 648
页数：5
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