基于聚类布尔矩阵的Apriori算法的研究

针对聚类布尔矩阵的Apriori算法—CBM_Apriori算法的不足之处,提出了一种基于聚类布尔矩阵的Eclat算法—CBM_Eclat算法。该算法首先对布尔矩阵使用K-medoids算法,获得权值和聚类后的布尔矩阵;然后将聚类后的布尔矩阵转换成Tidset,并采用逻辑"交操作"运算,进而有效地减少了聚类布尔矩阵存储和候选项集的生成,提高了该算法的执行效率。通过实例应用和算法执行结果都能够证明CBM_Eclat算法具有可行性和有效性。

The Research of Apriori Algorithm Based on Cluster Boolean Matrix

For the inadequacy of Apriori algorithm of cluster Boolean matrix —CBM_Apriori algorithm,this paper pres-ents a methods of Eclat algorithm based on cluster Boolean matrix —CBM_Eclat algorithm. To begin with, using K-medoids algorithm deal with Boolean matrix to obtain the weight and new Boolean matrix. Then,new Boolean ma-trix is transformed into the Tidset that use logical "and" operating,so the cluster Boolean matrix storage and candi-date itemsets are reduced effectively. Thus, the efficiency of the algorithm is improved. Meanwhile, the application of example and result of algorithm performance both can prove the feasibility and effectiveness of the CBM_Eclat algorithm.