【摘要】 对电子商务顾客忠诚度影响因素进行了全面的分析,以经典RFM客户忠诚度模型为基础,建立RFMSA电子商务客户忠诚度划分模型.通过聚类分析算法对顾客忠诚度进行划分.以经典聚类分析算法K-means为基础,提出分段确定初始聚类中心的改进算法对顾客忠诚度进行划.通过对经典样本数据进行分析,实验结果表明,改进的粗糙集K-means聚类算法能够有效的提高聚类的准确率.更多还原

【Abstract】 According to the characteristics of E-commerce industry,the influence factors of E-commerce customer loyalty were comprehensively analyzed. Based on classical RFM model based on customer loyalty,the customer loyalty of RFMSA E-commerce model was established. Based on the classical clustering analysis algorithm K-means,the improved algorithm of the initial cluster centers was proposed to partition the customer loyalty. Through the analysis of the classic sample data,the experimental results showed that the improved rough set K-means clustering algorithm could effectively improve the accuracy of clustering.更多还原