【摘要】 文中介绍了Apriori算法,并从逐渐减少扫描的数据量和减少扫描数据库的次数两个方面对Apriori算法进行优化,介绍了AprioriTid算法和Partition算法。根据这两种算法的优势又将两者进行结合,对整个数据库采用Partition算法,将数据库分区,而在每个分区中又采用AprioriTid算法。此外,在将数据库分区时,对数据进行一个预处理,即将支持数较高的两项集尽可能地放在同一个分区中,最后将结合的结果与单纯采用一种算法的效率进行比较。更多还原

【Abstract】 This paper introduces the Apriori Algorithm, optimizes the algorithm through the gradual reduction of the amounts of scan- ning data and the times of scanning database these two aspects, introduces the AprioriTid algorithm and Partition algorithm. According to the advantages of these two algorithms to combine the two again, using the Partition Algorithm for the whole database, though dividing the database into districts, each zone is used in AprioriTid algorithm. In addition, operates a data preprocessing while dividing the database into districts, that is to say, put the two sets of higher support into the same partition, and finally compares the efficiency of combining results with a simple algorithm.更多还原