Research on the construction and application of mobile application user data portrait based on improved K-means algorithm
Ping Zhou, Bowei Duan, Hang Tian, Feilong Liu, Xijing Li · 2023
At present, in the promotion and popularization of mobile applications, the application of user profiling technology is difficult and inefficient. In order to deepen the application of user profiling technology and reduce the difficulty of using user profiling technology, this paper proposes a hierarchical clustering user profiling construction model based on the improved K-means algorithm. The model focuses on constructing mobile application user features through hierarchical clustering algorithms to improve the computational speed and accuracy of user profiling model construction. Finally, the model is experimentally validated using a high-voltage power user sample set in the field of power marketing, The experimental results indicate that the hierarchical clustering user profile model can effectively improve the accuracy and computational speed of clustering and profile construction applications, making contributions to the promotion and application of user profile technology in power enterprises.