Data Mining Association Rules In The Research And Application

Data mining is an emerging research topic in database andartificial intelligence fields. It has attracted a great deal of attention in the information industry in recent years. The major reason is due to the wide applications ranging from business management, production control and market analysis to engineering design and science exploration.The task of mining association rules consists of two main steps. The first involves finding the set of all frequent itemsets. The second step involves testing and generating all high confidence rules among itemsets. For the both step, computable complexity is the bottleneck of the algorithm for the number of frequent itemsets increases with the number of items exponentially.So this paper provided a fast algorithm for mining associating rules in large database . Based on the traditional Apriori and other optimal algorithm , reaserched the character of them.We were not only develop the Adapted Step , but also improves the Apriori algorithm .The experimental results show that this algorithm out performs Apriori.In practical association mining ,there are many data with temporal constraint .So we have to mining association under temporal constraint .Although mining association with temporal constraint in practical situation ,we also have to meet some others constraint .For example profit constraint .To here the association can be more efficient to practical using .So this paper researched the characters of other algorithm and created a temporal association mining algorithm with the profit constraint within a valid life Periodicity Constraint Temporal FP-Growth (CT-FP-Growth ). This algorithm can not only discover the association within valid life periodical about different profit areas based on the interesting profiting constraint, but also can discover the valid time areas . Theory researching and lab result showed that the method is useful and efficient.At the end , to the association theory researching ,we used it to the Hospital Curing Decision Support System .To compare the efficience of the five kinds of medicals with same fuction, it is useful and efficient to helpe docters to make structions .