The Research And Realization Of Association Rules Data Mining Algorithms

Data Mining(DM)is a technique that aims to analyze and understand large source data and reveal knowledge hidden in the data. It has been viewed as an important evolution in information proeessing.During the past decade or over, the concepts and techniques on data mining have been presented,and especially in the latest few years.Some of them have been discussed in higher levels.Data Mining system can find lots of patterns,in which association rules describe the interesting relations among the items in given data sets.On the basis of association rules data mining,the algorithms'research is its key part for mining association rules.Many highly efficient algorithms in the field have been put forward for mining association rules so far.This paper gives a brief retrospect on the history of data mining technology.Based on the fundamental concepts of data mining technology,a detailed classification and summary on the objects of data mining have been carried out.In succession,this paper analyses and studies the current status of data mining technique and discusses its hot research fields.All of those provide a base for the overall expanding of this paper.Some useful algorithms presented by former researchers at first,were analysed and summarized in the thesis,and then we presented the new association rules algorithms for solving some relative problems in association rules data mining as follows:Firstly, an improved association rules updating algorithm UPA will be given.Through the UPA and FUP algorithm analysis ,and comparison of the experimental results show that UPA has better performance.Finally, an algorithm based on weighted FP-Tree for mining weighted maximum frequent itemsets ,WMFP will be presented. Also, this algorithm will be detailed well. Experimental result shows that the WMFP has effective and excellent expanding.To a certain extent the importance of different items in the database is solved.