Research On Algorithms For The Association Rules In Data Mining

Recently data mining is becoming much more important as the number of databases and database size keeps growing.Researchers in many different fields have shown great interest in data mining.the scope of data minming research is also extended to various fields.Association rules mining is one of the most hottest fields of data minming research.Data minming emerged as a rapidly growing technology in order to extract valuable information and knowledge in large volumes of data.Minming association rules is an important role of data minming because of its wide applicability in market analysis by expressing how tangible products and services relate to each other and how they rend to group together. nemThis dissertation systematically, deeply, roundly and detailed studies and analyses the data mining technique, especially the one for association rules. The main contents are listed as follows:Analyses and research of the data mining technique. the dissertation summarizes, analyses and studies the current status of the data mining technique in our native country and overseas widely and roundly and then summarizes and discusses its developmental trends and hot research fields. The definiteness and orientation of the data mining is reviewed in brief first. Based on the basic concepts of data mining, this dissertation classifies and summarizes the objects of data mining and the common techniques in detailed succession, all of the above become the basis for this dissertation.Analyses and research of the data mining technique for association rules. Based on the basic concepts of the association rules, analyses and studies the Apriori algorithms of association rules in detail. All kinds of optimized techniques which are designed to promote the algorithms efficiency are also studied and discussed in detail here. Based on the basic, the Apriori algorithm of riddling compression is proposed .And has carried on the simulation, the result demonstrated the Apriori algorithm of riddling compression can improve the efficiency greatly.besides,the paper proposes a tree structure algorithm based vertical tid-list to resolve the frequent itemsets program in Apriori, which combines the ordinal character of itemsets makes the nodes ascending order by support count in the tree ,so that the sets of the candidate frequent itemsets is the least totally . It can greatly reduce the candidate frequent itemsets, keeps the completion of frequent itemsets, reduces the cost of computing, and improve the efficiency of algorithm.