基于云模型理论的群体用户画像模型

Model of Group User Portrait Based on Cloud Model Theory

为了能够对群体用户中不确定性和模糊性的行为精确的定量分析和定性相似度的计算,设计了一个基于云模型理论的定性相似度算法来给群体用户构建画像模型.首先,采用识别客户价值最广泛的RFM(Recency,Frequency,Monetary)模型来细分用户.其次,通过云模型变换算法将用户的行为转换为用户的云模型标签,该云模型标签就是对用户行为的一次定量表示,然后通过云模型聚类算法来划分出不同的客户类型,作为客户画像的模型,利用该模型指导商业营销活动.

In order to quantitatively analyze and qualitatively calculate the uncertainty and ambiguity of group users accurately, in this study, a qualitative similarity algorithm based on cloud model theory is designed to build a portrait model for group users. Firstly, the user is divided by the most widely recognized RFM mode—Recency, Frequency, and Monetary. Secondly, the user＇s behavior is transformed into the user＇s cloud model label through the cloud model transformation algorithm. The cloud model label is a quantitative representation of user＇s behavior. Then, the cloud model clustering algorithm is used to classify different types of customers which are the model of customer portrait. Finally, the model is used to guide commercial marketing activities.