Associate rule minimization using boolean algebra set function

Abstract

Associated rule mining has become a common subject in data mining research field that is very popular used for marketing basket analysis. The discovery knowledge pattern mined can provide insight to the data holder as well as be invaluable in important task, such as decision making and strategic planning. This paper presents an associated rule mining technique that significantly helping for improvement of the decision making or planning. As a minimization mining strategy, we adopt the minimization using algebra set function and association rule mining methods. Our goal is to minimize the number of associated rule. This paper is of reviews preliminaries method presented a minimization algorithm and also tested with the well known data. The experimental results also show that our algorithm is an efficient method one. © 2014 IEEE.