Abstract: The algorithm of discovering association rules will be introduced to data mining of a large database of Chinese medicine formulations in order to find the association rules among the unilateral and binding medicine of Chinese medicine to provide an important basis for the development of new drugs.Since the Apriori which is a kind of association rules algorithm that commonly used has the shortcoming of scanning the database for many times.This paper presents a matrix-based algorithm of association rules Apriori_Matrix.The algorithm shortens the time spent in several comparisons in collection connection in Apriori algorithm，and can greatly improve efficiency of the association rules dig.For the limitation of the type of the unilateral in the traditional Chinese medicine database and great difference of compatibility rules and a variety of prescriptions corresponding one type of disease，improving algorithm can shorten the development cycle of new drugs.

摘要： 将关联规则发现算法引入到中药配方数据库的数据挖掘中，以求发现方剂中单方之间的关联规则及中药中的药对药组，可以为中药中新药的研制提供重要依据。由于常用的关联规则发现算法：Apriori算法存在多次扫描数据库的缺陷，提出了一种基于矩阵的关联规则发现算法：Apriori_Matrix算法，该算法优化了Apriori算法中集合连接过程多次比较所花费的时间，可极大地提高关联规则挖掘的效率。针对中药数据库中单方的种类有限、配伍规则各不相同、同一种病症对应多种方剂的情况，改进算法有助于缩短新药研制的周期。