Paper Title
Data Mining Technique for Reduction of Association Rules in Distributed System

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. Keywords - Association Rule Mining; Data Mining; Distributed Data Mining; Frequent Item Sets Mining; Reduction Framework.