Association Rules Algorithm And Its Application In Intelligent Pharmacy Systems Research

The association rule mining is an important research branch of the field of data mining, which has an irreplaceable role in finding the rules for the transaction data. In recent years, all domestic and foreign scholars, research institutions has invested a lot of energy on association rules algorithm itself and its application, put forward all kinds of algorithm in the original algorithm and the improvement. At the same time, the application of association rules is also deep into the various areas.This paper summarizes the research status of the data mining and association rules. It studies the Apriori algorithm of association rule mining and analyzes the main performance bottlenecks, then compares the advantages and disadvantages of the Apriori algorithm and FP-Growth algorithm, researches improvements based on data partitioning and hash-based algorithm.This paper analyzes the characteristics of Chinese medicine association rule mining, the norms, principles and superiority of the small package of Chinese Herbal Medicine in the pharmacy system. Construct the whole intelligence pharmacy PC software system, including the main control system, window system, stocking system, and realize the function module. Then, realize the association rules algorithm in configuration management position applications of pharmacy system. Elaborate the data processing operation, frequent itemsets discovery process and the positions of the specific distribution of principle. Compare the results and verify the superiority of the algorithm.Analyzes the existing problems in the paper, and pointed out the direction of further research.