Mining Association Rules Algorithm

Data mining is to extract or mine knowledge from large amount of data. So it is also called Knowledge Discovery in Database. It is a new subject that involves a lot of subjects and develops with these subjects. Data mining has several functions. Association analysis is one of the important functions.Association analysis is to find association rules. Association rules describe the interesting relations of the items in the given data set. At present, lots of algorithms for mining association rules have been brought forward. The most famous algorithms are Apriori and its transfiguration. These traditional algorithms often suffer from the bottleneck of itemset generation and difficultly confirm a suitable minimum support. In this paper, a new algorithm called Base-Weight is proposed to solve the above problems.Firstly, in this paper, we introduced the basic concept, problem existed and development way; Secondly, we introduced the basic concept, classification and some familiar algorithm ideas of association analysis. The idea of the classical algorithm Apriori is the emphasis and some of its transformative algorithms are introduced to improve the efficiency. In the end, to solve the problems existed in the traditional algorithms such as Apriori, a new algorithm called Base-Weight based on the seed item and weight is proposed. Its design idea, design process and performance study are discussed at large.