Data Mining Technique for Reduction of Association Rules in Distributed System

被引：0
|
作者：
Waghamare, Bhagyashri [1 ]
Bodhe, Yogesh [2 ]
机构：
[1] Shree Ramchandra Coll Engn, Dept Comp Engn, Pune, Maharashtra, India
[2] Dr DY Patil Sch Engn, Dept Comp Engn, Pune, Maharashtra, India
来源：
2016 INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND DYNAMIC OPTIMIZATION TECHNIQUES (ICACDOT) | 2016年
关键词：
Association Rule Mining; Data Mining; Distributed Data Mining; Frequent Item Sets Mining; Reduction Framework;
D O I：
暂无
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 today's world, there are number of transactions can be performed on social media. In such distributed environment where timely accessing of data is important, it becomes difficult to generate strong association rules. So it is necessary to reduce these rules for increasing rule reduction rate. This paper uses w-Tabular algorithm which combines weight assignment method and Quine-Mccluskey method which increases data processing time in distributed system.
引用
收藏
页码：415 / 418
页数：4
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