基于多维关联细粒度的电力信息化客户画像模型研究

Research on customer portrait model of power informatization based on multi-dimensional correlation and fine granularity

针对当前模型构建的客户画像对客户信息约束不足,导致客户画像模型拟合度较低的问题,提出了基于多维关联细粒度的电力营销信息化客户画像模型。根据电力营销客户画像信息需求和数据源,采集并预处理电力营销客户信息。采用多维关联细粒度,分析客户信息关联性,通过支持度和置信度,约束电力营销客户信息,结合CS算法和模糊均值算法,构建电力营销信息化客户画像模型。实验结果表明,所提模型的信息标准指数较为接近0,规范拟合指数和拟合优度指数较为接近1,能够有效提高客户画像模型拟合度。

To tackle the problem that the customer portrait constructed by the current model has insufficient constraints on customer information,resulting in the low fitting degree of the customer portrait model,a power marketing informatization customer portrait model based on multi-dimensional correlation and fine-grained is proposed.According to the power marketing customer portrait information needs and data sources,collect and preprocess the power marketing customer information.The multi-dimensional correlation fine-grained is used to analyze the relevance of customer information.The power marketing customer information is constrained through support and confidence.Combined with CS algorithm and fuzzy mean algorithm,the power marketing informatization customer portrait model is constructed.The experiment results show that the information standard index of the proposed model is close to 0,and the standard fitting index and goodness of fit index are close to 1,which can effectively improve the fitting degree of customer portrait model.