Intelligent Precision Recommendation Model of Digital Marketing Based On K-Means Algorithm

In view of the problem that the user clustering model for accurate digital marketing promotion is not comprehensive and in-depth, this paper uses the in-depth learning method to analyze the problem of the user clustering model for accurate digital marketing promotion. This method preprocesses and aggregates the image of short text through word segmentation and SIFT methods, and uses K-MEANS in-depth learning mode and Gibbs sampling method to establish and train the data clustering mode, so as to collect information such as customers' interests and preferences. The simulation operation on the inspection data set shows that this method can more comprehensively grasp the customer's attribute characteristics by aggregating image and text information than the ordinary method, thus playing a key role in accurate digital services.