Active children shoe recommending method based on preference correlation in online shopping environment

The invention provides an active children shoe recommending method based on preference correlation in an online shopping environment. The method consists of a model training stage and an online real-time recommending stage. The method comprises the following steps: at the model training stage, selecting a plurality of present popular children shoe products for extracting children shoe appearance elements, and performing clustering analysis on the appearance elements through a structural entropy clustering method to obtain a mainstream appearance type group; establishing a correlation model of customer individual characteristics and children shoe appearance types through multiple logistic methods, and performing optimization solution on correlation model parameters through network survey sample data; and at the online real-time recommending stage, automatically finding a children shoe appearance type which is most matched with customer characteristics according to the correlation model at the last stage by acquiring individual characteristic information of a customer in order to realize an active recommending function. Through adoption of the active children shoe recommending method, the effectiveness of the active recommending function in the online shopping environment can be enhanced, and technical support is provided for the enhancement of customer attention.