基于数据特征提取的线上电商用户潜在购买力挖掘方法

Method for Mining Potential Purchasing Power of Online E-commerce Users Based on Data Feature Extraction

为了更好实现线上电商用户潜在购买力挖掘,提出一种基于数据特征提取的线上电商用户潜在购买力挖掘方法.通过粗糙集组建线上电商用户访问数据的信息跟踪融合模型,采用模糊度特征分析方法重构线上电商用户访问数据,进而获取有关于用户潜在购买能力的关联特征.使用熵权决策法选择合适的权重,同时计算不同线上电商用户的潜在购买力,通过购买能力进行等级划分,最终实现电商用户潜在购买力挖掘.仿真实验结果表明,所提方法可以快速准确实现用户购买力挖掘.

In order to better realize the mining of the potential purchasing power of online e-commerce users,a method for mining the potential purchasing power of online e-commerce users based on data feature extraction is proposed.The information tracking fusion model of online e-commerce user access data is constructed by rough set,and the online e-commerce user access data is reconstructed by the method of ambiguity feature analysis,and then the associated features about the potential purchasing power of users are obtained.Used the entropy decision method the appropriate weights is selected,and the potential purchasing power of different online e-commerce users is calculated at the same time,and through classified the purchasing power through the level of purchasing power,the potential purchasing power of e-commerce users is finally realized.Simulation experiment results show that the proposed method can quickly and accurately realize user purchasing power mining.